wiroai-turkish-llm-9b-GGUF

Name: wiroai-turkish-llm-9b-GGUF
Author: QuantFactory

208

—

QuantFactory

Language Model

OTHER

9B params

New

208 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

21GB+ RAM

Mobile

Laptop

Server

Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

9GB+ RAM

Code Examples

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

Usagepythontransformers

import transformers
import torch


model_id = "WiroAI/wiroai-turkish-llm-9b"

pipeline = transformers.pipeline(
    "text-generation",
    model=model_id,
    model_kwargs={"torch_dtype": torch.bfloat16},
    device_map="auto",
)

pipeline.model.eval()
instruction = "Bana İstanbul ile alakalı bir sosyal medya postu hazırlar mısın?"

messages = [
    {"role": "user", "content": f"{instruction}"}
]

prompt = pipeline.tokenizer.apply_chat_template(
    messages, 
    tokenize=False, 
    add_generation_prompt=True
)

terminators = [
    pipeline.tokenizer.eos_token_id,
    pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
]

outputs = pipeline(
    prompt,
    max_new_tokens=512,
    eos_token_id=terminators,
    do_sample=True,
    temperature=0.9,
)

print(outputs[0]["generated_text"][len(prompt):])

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