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update cli_internlm2.py
three methods to load model 1. download model in openxlab 2. download model in modelscope 3. offline model
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demo/cli_internlm2.py

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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from openxlab.model import download
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from modelscope import snapshot_download
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download(model_repo='jujimeizuo/EmoLLM_Model',
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output='model')
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# download model in openxlab
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model_name_or_path =download(model_repo='ajupyter/EmoLLM_internlm2_7b_full',
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output='EmoLLM_internlm2_7b_full')
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model_name_or_path = "model"
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# download model in modelscope
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model_name_or_path = snapshot_download('chg0901/EmoLLM-InternLM7B-base')
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# offline model
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# model_name_or_path = "/root/StableCascade/emollm2/EmoLLM/xtuner_config/merged"
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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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system_prompt = '你是心理健康助手EmoLLM,由EmoLLM团队打造。你旨在通过专业心理咨询,协助来访者完成心理诊断。请充分利用专业心理学知识与咨询技术,一步步帮助来访者解决心理问题。'
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messages = [(system_prompt, '')]
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