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@ -175,9 +175,9 @@ print(tokenizer.decode(pred.cpu()[0], skip_special_tokens=True))
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from modelscope import AutoModelForCausalLM, AutoTokenizer
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from modelscope import GenerationConfig
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tokenizer = AutoTokenizer.from_pretrained("qwen/Qwen-7B-Chat", revision = 'v1.0.5',trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("qwen/Qwen-7B-Chat", revision = 'v1.0.5',device_map="auto", trust_remote_code=True,fp16 = True).eval()
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model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat",revision = 'v1.0.5', trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
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tokenizer = AutoTokenizer.from_pretrained("qwen/Qwen-7B-Chat", revision='v1.0.5', trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("qwen/Qwen-7B-Chat", revision='v1.0.5', device_map="auto", trust_remote_code=True, fp16=True).eval()
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model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", revision='v1.0.5', trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参
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response, history = model.chat(tokenizer, "你好", history=None)
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print(response)
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