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---
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language:
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- zh
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- en
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tags:
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- MachineMindset
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- MBTI
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pipeline_tag: text-generation
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inference: false
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---
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<p align="center">
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<img src="https://raw.githubusercontent.com/PKU-YuanGroup/Machine-Mindset/main/images/logo.png" width="650" style="margin-bottom: 0.2;"/>
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<p>
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<h2 align="center"> <a href="https://arxiv.org/abs/2311.10122">Machine Mindset: An MBTI Exploration of Large Language Models</a></h2>
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<h5 align="center"> If you like our project, please give us a star ⭐ </h2>
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<h4 align="center"> [ 中文 | <a href="https://huggingface.co/FarReelAILab/Machine_Mindset_en_INFP">English</a> | <a href="https://github.com/PKU-YuanGroup/Machine-Mindset/blob/main/README_ja.md">日本語</a> ]
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<br>
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### 介绍 (Introduction)
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**MM_zh_INFP (Machine_Mindset_zh_INFP)** 是FarReel AI Lab和北大深研院合作研发的基于Baichuan-7b-chat的MBTI类型为INFP的中文大模型。
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MM_zh_INFP经过我们自主构建的大规模MBTI数据集,经多阶段的微调和DPO训练而来。我们会持续将模型更新到效果更优的版本、并不断补充测试数据。本仓库为MM_zh_INFP模型的仓库。
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MM_zh_INFP (Machine_Mindset_zh_INFP)的基础性格特征是**INFP**,更详细的性格描述见[16personalities](https://www.16personalities.com/)。
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如果您想了解更多关于Machine_Mindset开源模型的细节,我们建议您参阅[GitHub代码库](https://github.com/PKU-YuanGroup/Machine-Mindset/)。
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### 要求(Requirements)
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* python 3.8及以上版本
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* pytorch 1.12及以上版本,推荐2.0及以上版本
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* 建议使用CUDA 11.4及以上(GPU用户、flash-attention用户等需考虑此选项)
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<br>
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### 快速使用(Quickstart)
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* 使用HuggingFace Transformers库(单轮对话):
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers.generation.utils import GenerationConfig
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tokenizer = AutoTokenizer.from_pretrained("FarReelAILab/Machine_Mindset_zh_INFP", use_fast=False, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("FarReelAILab/Machine_Mindset_zh_INFP", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
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model.generation_config = GenerationConfig.from_pretrained("FarReelAILab/Machine_Mindset_zh_INFP")
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messages = []
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messages.append({"role": "user", "content": "你的MBTI人格是什么"})
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response = model.chat(tokenizer, messages)
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print(response)
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messages.append({'role': 'assistant', 'content': response})
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messages.append({"role": "user", "content": "和一群人聚会一天回到家,你会是什么感受"})
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response = model.chat(tokenizer, messages)
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print(response)
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```
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* 使用HuggingFace Transformers库(多轮对话):
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers.generation.utils import GenerationConfig
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tokenizer = AutoTokenizer.from_pretrained("FarReelAILab/Machine_Mindset_zh_INFP", use_fast=False, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("FarReelAILab/Machine_Mindset_zh_INFP", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
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model.generation_config = GenerationConfig.from_pretrained("FarReelAILab/Machine_Mindset_zh_INFP")
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messages = []
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print("####Enter 'exit' to exit.")
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print("####Enter 'clear' to clear the chat history.")
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while True:
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user=str(input("User:"))
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if user.strip()=="exit":
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break
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elif user.strip()=="clear":
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messages=[]
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continue
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messages.append({"role": "user", "content": user})
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response = model.chat(tokenizer, messages)
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print("Assistant:", response)
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messages.append({"role": "assistant", "content": str(response)})
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```
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* 使用LLaMA-Factory推理框架(多轮对话)
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```bash
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git clone https://github.com/hiyouga/LLaMA-Factory.git
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cd LLaMA-Factory
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python ./src/cli_demo.py \
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--model_name_or_path /path_to_your_local_model \
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--template baichuan2 #如果您使用的是中文模型,template须指定为baichuan2;如果您使用的是英文模型,template须指定为llama2
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```
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关于更多的使用说明,请参考我们的[GitHub代码库](https://github.com/PKU-YuanGroup/Machine-Mindset/)获取更多信息。
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<br>
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### 引用 (Citation)
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如果你觉得我们的工作对你有帮助,欢迎引用!
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```
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@article{cui2023machine,
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title={Machine Mindset: An MBTI Exploration of Large Language Models},
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author={Cui, Jiaxi and Lv, Liuzhenghao and Wen, Jing and Tang, Jing and Tian, YongHong and Yuan, Li},
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journal={arXiv preprint arXiv:2312.12999},
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year={2023}
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}
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```
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<br>
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### 使用协议(License Agreement)
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我们的代码遵循Apache2.0协议开源。请查看[LICENSE](https://github.com/PKU-YuanGroup/Machine-Mindset/blob/main/LICENSE)了解具体的开源协议细节。
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我们的模型权重基于原始基础模型权重的开源协议。
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中文版本是基于baichuan的开源协议细节,支持商用。请查看[model_LICENSE](https://huggingface.co/JessyTsu1/Machine_Mindset_zh_INFP/resolve/main/Machine_Mindset%E5%9F%BA%E4%BA%8Ebaichuan%E7%9A%84%E6%A8%A1%E5%9E%8B%E7%A4%BE%E5%8C%BA%E8%AE%B8%E5%8F%AF%E5%8D%8F%E8%AE%AE.pdf)查看具体细节。
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英文版基于[llama2的开源协议](https://ai.meta.com/resources/models-and-libraries/llama-downloads/)
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### 联系我们(Contact Us)
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如果您有任何问题,请邮件联系jiaxicui446@gmail.com,lvliuzh@stu.pku.edu.cn
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