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--- |
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license: llama3 |
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--- |
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## how to use |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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DEFAULT_SYSTEM_PROMPT = "あなたは誠実で優秀な日本人のアシスタントです。特に指示が無い場合は、常に日本語で回答してください。" |
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text = "優秀なAIとはなんですか? またあなたの考える優秀なAIに重要なポイントを5つ挙げて下さい。" |
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model_name = "TeamDelta/llama3-8B-test" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name, |
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torch_dtype="auto", |
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device_map="auto", |
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) |
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model.eval() |
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messages = [ |
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{"role": "system", "content": DEFAULT_SYSTEM_PROMPT}, |
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{"role": "user", "content": text}, |
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] |
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prompt = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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token_ids = tokenizer.encode( |
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prompt, add_special_tokens=False, return_tensors="pt" |
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) |
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with torch.no_grad(): |
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output_ids = model.generate( |
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token_ids.to(model.device), |
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max_new_tokens=1200, |
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do_sample=True, |
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temperature=0.6, |
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top_p=0.9, |
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) |
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output = tokenizer.decode( |
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output_ids.tolist()[0][token_ids.size(1):], skip_special_tokens=True |
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) |
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print(output) |
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``` |
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