2024-01-23 08:41:15 +08:00
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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2024-01-27 08:49:17 +08:00
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from openxlab.model import download
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2024-01-23 08:41:15 +08:00
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2024-01-27 08:49:17 +08:00
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download(model_repo='jujimeizuo/EmoLLM_Model',
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output='model')
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2024-01-23 08:41:15 +08:00
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2024-01-27 08:49:17 +08:00
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model_name_or_path = "model"
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2024-01-23 08:41:15 +08:00
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tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(model_name_or_path, trust_remote_code=True, torch_dtype=torch.bfloat16, device_map='auto')
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model = model.eval()
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system_prompt = "你是一个由aJupyter、Farewell、jujimeizuo、Smiling&Weeping研发（排名按字母顺序排序，不分先后）、散步提供技术支持、上海人工智能实验室提供支持开发的心理健康大模型。现在你是一个心理专家，我有一些心理问题，请你用专业的知识帮我解决。"
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messages = [(system_prompt, '')]
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print("=============Welcome to InternLM chatbot, type 'exit' to exit.=============")
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while True:
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input_text = input("User >>> ")
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input_text.replace(' ', '')
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if input_text == "exit":
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break
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response, history = model.chat(tokenizer, input_text, history=messages)
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messages.append((input_text, response))
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print(f"robot >>> {response}")
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