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--- |
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license: llama3 |
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language: |
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- tr |
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pipeline_tag: text-generation |
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--- |
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## Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
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model_id = "Trendyol/Trendyol-LLM-8b-chat-v2.0" |
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pipe = pipeline( |
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"text-generation", |
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model=model_id, |
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model_kwargs={ |
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"torch_dtype": torch.bfloat16, |
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"use_cache":True, |
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"use_flash_attention_2": True |
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}, |
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device_map='auto', |
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) |
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terminators = [ |
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pipe.tokenizer.eos_token_id, |
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pipe.tokenizer.convert_tokens_to_ids("<|eot_id|>") |
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] |
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sampling_params = dict(do_sample=True, temperature=0.3, top_k=50, top_p=0.9, repetition_penalty=1.1) |
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DEFAULT_SYSTEM_PROMPT = "Sen yardımsever bir asistansın ve sana verilen talimatlar doğrultusunda en iyi cevabı üretmeye çalışacaksın." |
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def generate_output(user_query, sys_prompt=DEFAULT_SYSTEM_PROMPT): |
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messages = [ |
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{"role": "system", "content": sys_prompt}, |
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{"role": "user", "content": user_query} |
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] |
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outputs = pipe( |
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messages, |
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max_new_tokens=1024, |
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eos_token_id=terminators, |
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return_full_text=False, |
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**sampling_params |
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) |
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return outputs[0]["generated_text"] |
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response = generate_output("Türkiye'de kaç il var?") |
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print(response) |
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``` |