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license: apache-2.0 |
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language: |
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- zh |
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pipeline_tag: text-generation |
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--- |
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How to use： |
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------ |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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import torch |
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model_id = "BoyangZ/Llama3-chinese_chat_ft" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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torch_dtype=torch.bfloat16, |
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device_map="auto", |
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) |
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messages = [ |
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{"role": "system", "content": "You are a LLM assistant. Users will ask you questions in Chinese, You will answer questions in Chinese"}, |
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{"role": "user", "content": "李白是哪个朝代的人?"}, |
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] |
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input_ids = tokenizer.apply_chat_template( |
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messages, |
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add_generation_prompt=True, |
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return_tensors="pt" |
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).to(model.device) |
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terminators = [ |
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tokenizer.eos_token_id, |
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tokenizer.convert_tokens_to_ids("<|eot_id|>") |
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] |
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outputs = model.generate( |
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input_ids, |
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max_new_tokens=256, |
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eos_token_id=terminators, |
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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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response = outputs[0][input_ids.shape[-1]:] |
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print(tokenizer.decode(response, skip_special_tokens=True)) |
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example1 |
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example2 |
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example3 |
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