ReasoningCore-3B-Instruct-r01-Reflect-Math

1
1
3.0B
2 languages
llama
by
EpistemeAI
Language Model
OTHER
3B params
New
1 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
7GB+ RAM
Mobile
Laptop
Server
Quick Summary

This is a reasoning and reflect instruction-tuned generative model in 3B size (text in/text out).

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
3GB+ RAM

Code Examples

pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
pythontransformers
import torch
from transformers import pipeline

model_id = "EpistemeAI/ReasoningCore-3B-Instruct-r01-Reflect-Math"
pipe = pipeline(
    "text-generation",
    model=model_id,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)
messages = [
    {"role": "system", "content": "You are a powerful assistant Respond in the following format:
<reasoning>
...
</reasoning>
<reflecting>
...
</reflecting>
<answer>
...
</answer>"},
    {"role": "user", "content": "Which is bigger? 9.11 or 9.9?"},
]
outputs = pipe(
    messages,
    max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])

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