K2-Think
9.6K
359
131K
Long context
20.9B
1 language
license:apache-2.0
by
LLM360
Language Model
OTHER
New
10K downloads
Early-stage
Edge AI:
Mobile
Laptop
Server
47GB+ RAM
Mobile
Laptop
Server
Quick Summary
--- base_model: Qwen/Qwen2.
Device Compatibility
Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
20GB+ RAM
Code Examples
pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])pythontransformers
from transformers import pipeline
import torch
model_id = "LLM360/K2-Think"
pipe = pipeline(
"text-generation",
model=model_id,
torch_dtype="auto",
device_map="auto",
)
messages = [
{"role": "user", "content": "what is the next prime number after 2600?"},
]
outputs = pipe(
messages,
max_new_tokens=32768,
)
print(outputs[0]["generated_text"][-1])Deploy This Model
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