初始化项目,由ModelHub XC社区提供模型
Model: aJupyter/EmoLLM-LLaMA3_8b_instruct_aiwei Source: Original Platform
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<div align="center">
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# EmoLLM-心理健康大模型
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</div>
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<p align="center">
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<a href="https://github.com/SmartFlowAI/EmoLLM/">
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<img src="assets/EmoLLM_transparent.png" alt="Logo" width="50%">
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</a>
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<div align="center">
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<!-- PROJECT SHIELDS -->
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[![Contributors][contributors-shield]][contributors-url]
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[![Forks][forks-shield]][forks-url]
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[![Issues][issues-shield]][issues-url]
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[![OpenXLab_App][OpenXLab_App-image]][OpenXLab_App-url]
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[![OpenXLab_Model][OpenXLab_Model-image]][OpenXLab_Model-url]
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[![MIT License][license-shield]][license-url]
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[![Stargazers][stars-shield]][stars-url]
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</div>
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<h3 align="center">EmoLLM</h3>
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<div align="center">
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简体中文| <a href="README_EN.md" >English</a>
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<br />
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<br />
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<a href="https://github.com/SmartFlowAI/EmoLLM"><strong>探索本项目的文档 »</strong></a>
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<br />
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<br />
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<a href="https://openxlab.org.cn/apps/detail/Farewell1/EmoLLMV2.0">体验EmoLLM 2.0</a>
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·
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<a href="https://github.com/SmartFlowAI/EmoLLM/issues">报告Bug</a>
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·
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<a href="https://github.com/SmartFlowAI/EmoLLM/issues">提出新特性</a>
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</div>
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<!-- 本篇README.md面向开发者 -->
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**EmoLLM** 是一系列能够支持 **理解用户-支持用户-帮助用户** 心理健康辅导链路的心理健康大模型,由 `LLM`指令微调而来,欢迎大家star~⭐⭐。目前已经开源的 `LLM` 微调配置如下:
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<div align="center">
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| 模型 | 类型 | 链接 |
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| :-------------------: | :------: | :------------------------------------------------------------------------------------------------------: |
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| InternLM2_7B_chat | QLORA | [internlm2_7b_chat_qlora_e3.py](./xtuner_config/internlm2_7b_chat_qlora_e3.py) |
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| InternLM2_7B_chat | 全量微调 | [internlm2_chat_7b_full.py](./xtuner_config/internlm2_chat_7b_full.py) |
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| InternLM2_7B_base | QLORA | [internlm2_7b_base_qlora_e10_M_1e4_32_64.py](./xtuner_config/internlm2_7b_base_qlora_e10_M_1e4_32_64.py) |
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| InternLM2_1_8B_chat | 全量微调 | [internlm2_1_8b_full_alpaca_e3.py](./xtuner_config/internlm2_1_8b_full_alpaca_e3.py) |
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| InternLM2_20B_chat | LORA |[internlm2_20b_chat_lora_alpaca_e3.py](./xtuner_config/internlm2_20b_chat_lora_alpaca_e3.py)|
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| Qwen_7b_chat | QLORA | [qwen_7b_chat_qlora_e3.py](./xtuner_config/qwen_7b_chat_qlora_e3.py) |
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| Qwen1_5-0_5B-Chat | 全量微调 | [qwen1_5_0_5_B_full.py](./xtuner_config/qwen1_5_0_5_B_full.py) |
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| Baichuan2_13B_chat | QLORA | [baichuan2_13b_chat_qlora_alpaca_e3.py](./xtuner_config/baichuan2_13b_chat_qlora_alpaca_e3.py) |
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| ChatGLM3_6B | LORA | [chatglm3_6b_lora_alpaca_e3.py](./xtuner_config/chatglm3_6b_lora_alpaca_e3.py) |
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| DeepSeek MoE_16B_chat | QLORA | [deepseek_moe_16b_chat_qlora_oasst1_e3.py](./xtuner_config/deepseek_moe_16b_chat_qlora_oasst1_e3.py) |
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| Mixtral 8x7B_instruct | QLORA | [mixtral_8x7b_instruct_qlora_oasst1_e3.py](./xtuner_config/mixtral_8x7b_instruct_qlora_oasst1_e3.py) |
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| …… | …… | …… |
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</div>
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欢迎大家为本项目做出贡献~
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---
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心理健康大模型(Mental Health Grand Model)是一个综合性的概念,它旨在全面理解和促进个体、群体乃至整个社会的心理健康状态。这个模型通常包含以下几个关键组成部分:
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- 认知因素:涉及个体的思维模式、信念系统、认知偏差以及解决问题的能力。认知因素对心理健康有重要影响,因为它们影响个体如何解释和应对生活中的事件。
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- 情感因素:包括情绪调节、情感表达和情感体验。情感健康是心理健康的重要组成部分,涉及个体如何管理和表达自己的情感,以及如何从负面情绪中恢复。
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- 行为因素:涉及个体的行为模式、习惯和应对策略。这包括应对压力的技巧、社交技能以及自我效能感,即个体对自己能力的信心。
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- 社会环境:包括家庭、工作、社区和文化背景等外部因素,这些因素对个体的心理健康有着直接和间接的影响。
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- 生理健康:身体健康与心理健康紧密相关。良好的身体健康可以促进心理健康,反之亦然。
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- 心理韧性:指个体在面对逆境时的恢复力和适应能力。心理韧性强的人更能够从挑战中恢复,并从中学习和成长。
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- 预防和干预措施:心理健康大模型还包括预防心理问题和促进心理健康的策略,如心理教育、心理咨询、心理治疗和社会支持系统。
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- 评估和诊断工具:为了有效促进心理健康,需要有科学的工具来评估个体的心理状态,以及诊断可能存在的心理问题。
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<table>
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<tr>
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<td align="center" style="background-color: transparent">
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<img src="assets\aiwei_demo.gif" alt="占位图">
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</td>
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<td align="center" style="background-color: transparent">
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<img src="assets\aiwei_demo2.gif" alt="占位图">
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</td>
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</tr>
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<tr>
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<td align="center" style="background-color: transparent">
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<img src="assets\aiwei_demo3.gif" alt="占位图">
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</td>
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<td align="center" style="background-color: transparent">
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<img src="assets\aiwei_demo4.gif" alt="占位图">
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</td>
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</tr>
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</table>
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### 🎇最近更新
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- 【2024.4.2】在 Huggingface 上传[老母亲心理咨询师](https://huggingface.co/brycewang2018/EmoLLM-mother/tree/main)
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- 【2024.3.25】在百度飞桨平台发布[爹系男友心理咨询师](https://aistudio.baidu.com/community/app/68787)
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- 【2024.3.24】在**OpenXLab**和**ModelScope**平台发布**InternLM2-Base-7B QLoRA微调模型**, 具体请查看[**InternLM2-Base-7B QLoRA**](./xtuner_config/README_internlm2_7b_base_qlora.md)
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- 【2024.3.12】在百度飞桨平台发布[艾薇](https://aistudio.baidu.com/community/app/63335)
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- 【2024.3.11】 **EmoLLM V2.0 相比 EmoLLM V1.0 全面提升,已超越 Role-playing ChatGPT 在心理咨询任务上的能力!**[点击体验EmoLLM V2.0](https://openxlab.org.cn/apps/detail/Farewell1/EmoLLMV2.0),更新[数据集统计及详细信息](./datasets/)、[路线图](./assets/Roadmap_ZH.png)
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- 【2024.3.9】 新增并发功能加速 [QA 对生成](./scripts/qa_generation/)、[RAG pipeline](./rag/)
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- 【2024.3.3】 [基于InternLM2-7B-chat全量微调版本EmoLLM V2.0开源](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_internlm2_7b_full),需要两块A100*80G,更新专业评估,详见[evaluate](./evaluate/),更新基于PaddleOCR的PDF转txt工具脚本,详见[scripts](./scripts/)
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- 【2024.2.29】更新客观评估计算,详见[evaluate](./evaluate/),更新一系列数据集,详见[datasets](./datasets/)
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- 【2024.2.27】更新英文readme和一系列数据集(舔狗和单轮对话)
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- 【2024.2.23】推出基于InternLM2_7B_chat_qlora的 `温柔御姐心理医生艾薇`,[点击获取模型权重](https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_aiwei),[配置文件](xtuner_config/aiwei-internlm2_chat_7b_qlora.py),[在线体验链接](https://openxlab.org.cn/apps/detail/ajupyter/EmoLLM-aiwei)
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- 【2024.2.23】更新[若干微调配置](/xtuner_config/),新增 [data_pro.json](/datasets/data_pro.json)(数量更多、场景更全、更丰富)和 [aiwei.json](/datasets/aiwei.json)(温柔御姐角色扮演专用,带有Emoji表情),即将推出 `温柔御姐心理医生艾薇`
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- 【2024.2.18】 [基于Qwen1_5-0_5B-Chat全量微调版本开源](https://www.modelscope.cn/models/aJupyter/EmoLLM_Qwen1_5-0_5B-Chat_full_sft/summary),算力有限的道友可以玩起来~
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<details>
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<summary>查看更多</summary>
|
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- 【2024.2.6】 EmoLLM在[**Openxlab** ](https://openxlab.org.cn/models/detail/jujimeizuo/EmoLLM_Model) 平台下载量高达18.7k,欢迎大家体验!
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<p align="center">
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<img src="https://github.com/SmartFlowAI/EmoLLM/assets/62385492/7e931682-c54d-4ded-bc67-79130c68d744" alt="模型下载量">
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</p>
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- 【2024.2.5】 项目荣获公众号**NLP工程化**推文宣传[推文链接](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A),为博主推广一波,欢迎大家关注!!🥳🥳
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<p align="center">
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<img src="https://github.com/SmartFlowAI/EmoLLM/assets/62385492/47868d6a-2e91-4aa9-a630-e594c14295b4" alt="公众号二维码">
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</p>
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- 【2024.2.3】 [项目宣传视频](https://www.bilibili.com/video/BV1N7421N76X/)完成 😊
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- 【2024.1.27】 完善数据构建文档、微调指南、部署指南、Readme等相关文档 👏
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- 【2024.1.25】 EmoLLM V1.0 已部署上线 https://openxlab.org.cn/apps/detail/jujimeizuo/EmoLLM 😀
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</details>
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### 🏆荣誉栏
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- 项目荣获上海人工智能实验室举办的**2024浦源大模型系列挑战赛春季赛*****创新创意奖***
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<p align="center">
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<a href="https://github.com/SmartFlowAI/EmoLLM/">
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<img src="assets/Shusheng.png" alt="浦语挑战赛创新创意奖">
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</p>
|
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|
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- 项目荣获公众号**NLP工程化**[推文宣传](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A)
|
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### 🎯路线图
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<p align="center">
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<a href="https://github.com/SmartFlowAI/EmoLLM/">
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<img src="assets/Roadmap_ZH.png" alt="Roadmap_ZH">
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</a>
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### 🔗框架图
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<p align="center">
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<a href="https://github.com/SmartFlowAI/EmoLLM/">
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<img src="assets/框架图.png" alt="Framework_ZH">
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</a>
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## 目录
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- [EmoLLM-心理健康大模型](#emollm-心理健康大模型)
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- [🎇最近更新](#最近更新)
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- [🏆荣誉栏](#荣誉栏)
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- [🎯路线图](#路线图)
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- [🔗框架图](#框架图)
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- [目录](#目录)
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- [开发前的配置要求](#开发前的配置要求)
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- [**使用指南**](#使用指南)
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- [🍪快速体验](#快速体验)
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- [📌数据构建](#数据构建)
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- [🎨微调指南](#微调指南)
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- [🔧部署指南](#部署指南)
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- [⚙RAG(检索增强生成)Pipeline](#rag检索增强生成pipeline)
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- [使用到的框架](#使用到的框架)
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- [如何参与本项目](#如何参与本项目)
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- [作者(排名不分先后)](#作者排名不分先后)
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- [版权说明](#版权说明)
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- [引用](#引用)
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- [特别鸣谢](#特别鸣谢)
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- [Star History](#star-history)
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- [🌟 Contributors](#-contributors)
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- [交流群](#交流群)
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###### 开发前的配置要求
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- 硬件:A100 40G(仅针对InternLM2_7B_chat+qlora微调+deepspeed zero2优化)
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###### **使用指南**
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1. Clone the repo
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```sh
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git clone https://github.com/SmartFlowAI/EmoLLM.git
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```
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2. 依次阅读或者选择感兴趣的部分阅读:
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- [快速体验](#快速体验)
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- [数据构建](#数据构建)
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- [微调指南](#微调指南)
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- [部署指南](#部署指南)
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- [RAG](#rag检索增强生成pipeline)
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- 查看更多详情
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### 🍪快速体验
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- 请阅读[快速体验](docs/quick_start.md)查阅
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### 📌数据构建
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- 请阅读[数据构建指南](generate_data/tutorial.md)查阅
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- 微调用到的数据集见[datasets](datasets/data.json)
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### 🎨微调指南
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详见[微调指南](xtuner_config/README.md)
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### 🔧部署指南
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- Demo部署:详见[部署指南](demo/README.md)
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- 基于[LMDeploy](https://github.com/InternLM/lmdeploy/)的量化部署:详见[deploy](./deploy/lmdeploy.md)
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### ⚙RAG(检索增强生成)Pipeline
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- 详见[RAG](./rag/)
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<details>
|
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<summary>更多详情</summary>
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||||
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### 使用到的框架
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- [Xtuner](https://github.com/InternLM/xtuner):用于微调
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- [Transformers](https://github.com/huggingface/transformers)
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- [Pytorch](https://pytorch.org/)
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- [LMDeploy](https://github.com/InternLM/lmdeploy/):用于量化部署
|
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- [Stremlit](https://streamlit.io/):用于构建Demo
|
||||
- [DeepSpeed](https://github.com/microsoft/DeepSpeed):并行训练
|
||||
- …
|
||||
|
||||
#### 如何参与本项目
|
||||
|
||||
贡献使开源社区成为一个学习、激励和创造的绝佳场所。你所作的任何贡献都是**非常感谢**的。
|
||||
|
||||
1. Fork the Project
|
||||
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
|
||||
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
|
||||
4. Push to the Branch (`git push origin feature/AmazingFeature`)
|
||||
5. Open a Pull Request
|
||||
|
||||
</details>
|
||||
|
||||
### 作者(排名不分先后)
|
||||
|
||||
| 用户名 | 学校/组织 | 备注 | 贡献 |
|
||||
| :----------------------------------------------------------: | :------------------------------------------------: | :----------------------------------------------------------: | :-------------------------------------------: |
|
||||
| [aJupyter](https://github.com/aJupyter) | 南开大学在读硕士 | DataWhale成员 | 项目发起人 |
|
||||
| [MING-ZCH](https://github.com/MING-ZCH) | 华中科技大学在读本科生 | LLM x Psychology 研究者 | 项目联合负责人 |
|
||||
| [jujimeizuo](https://github.com/jujimeizuo) | 江南大学在读硕士 | | |
|
||||
| [Smiling-Weeping-zhr](https://github.com/Smiling-Weeping-zhr) | 哈尔滨工业大学(威海)在读本科生 | | |
|
||||
| [8baby8](https://github.com/8baby8) | 飞桨领航团区域主管 | 文心大模型核心开发者 | |
|
||||
| [zxazys](https://github.com/zxazys) | 南开大学在读硕士 | | |
|
||||
| [JasonLLLLLLLLLLL](https://github.com/JasonLLLLLLLLLLL) | swufe | | |
|
||||
| [MrCatAI](https://github.com/MrCatAI) | AI搬用工 | | |
|
||||
| [ZeyuBa](https://github.com/ZeyuBa) | 自动化所在读硕士 | | |
|
||||
| [aiyinyuedejustin](https://github.com/aiyinyuedejustin) | 宾夕法尼亚大学在读硕士 | | |
|
||||
| [Nobody-ML](https://github.com/Nobody-ML) | 中国石油大学(华东)在读本科生 | | |
|
||||
| [chg0901](https://github.com/chg0901) | [MiniSora](https://github.com/mini-sora/minisora/) | [MiniSora](https://github.com/mini-sora/minisora/)主要维护者,管理员 | LLM预训练和微调、模型上传、数据清洗、文档翻译 |
|
||||
| [Mxoder](https://github.com/Mxoder) | 北京航空航天大学在读本科生 | | |
|
||||
| [Anooyman](https://github.com/Anooyman) | 南京理工大学硕士 | | |
|
||||
| [Vicky-3021](https://github.com/Vicky-3021) | 西安电子科技大学硕士(研0) | | |
|
||||
| [SantiagoTOP](https://github.com/santiagoTOP) | 太原理工大学在读硕士 | | 数据清洗,文档管理、Baby EmoLLM维护 |
|
||||
| [zealot52099](https://github.com/zealot52099) | 个人开发者 | | 清洗数据、LLM微调、RAG |
|
||||
| [wwwyfff](https://github.com/wwwyfff) | 复旦大学在读硕士 | | |
|
||||
| [Yicooong](https://github.com/Yicooong) | 南开大学在读硕士 | | |
|
||||
| [jkhumor](https://github.com/jkhumor) | 南开大学在读硕士 | | RAG |
|
||||
| [lll997150986](https://github.com/lll997150986) | 南开大学在读硕士 | | 微调 |
|
||||
| [nln-maker](https://github.com/nln-maker) | 南开大学在读硕士 | | 前后端开发 |
|
||||
| [dream00001](https://github.com/dream00001) | 南开大学在读硕士 | | 前后端开发 |
|
||||
| [王几行XING](https://zhihu.com/people/brycewang1898) | 北京大学硕士毕业 | | 清洗数据、LLM微调、前后端开发 |
|
||||
| [思在] | 北京大学硕士毕业(微软美国) | | LLM微调、前后端开发 |
|
||||
|
||||
### 版权说明
|
||||
|
||||
该项目签署了 MIT 授权许可,详情请参阅 [LICENSE](https://github.com/SmartFlowAI/EmoLLM/blob/main/LICENSE)
|
||||
|
||||
### 引用
|
||||
|
||||
如果本项目对您的工作有所帮助,请使用以下格式引用:
|
||||
|
||||
```bibtex
|
||||
@misc{EmoLLM,
|
||||
title={EmoLLM},
|
||||
author={EmoLLM},
|
||||
url={https://github.com/SmartFlowAI/EmoLLM/},
|
||||
year={2024}
|
||||
}
|
||||
```
|
||||
|
||||
### 特别鸣谢
|
||||
|
||||
- [Sanbu](https://github.com/sanbuphy)
|
||||
- [上海人工智能实验室](https://www.shlab.org.cn/)
|
||||
- [闻星大佬(小助手)](https://github.com/vansin)
|
||||
- [扫地升(公众号宣传)](https://mp.weixin.qq.com/s/78lrRl2tlXEKUfElnkVx4A)
|
||||
- 阿布(北大心理学硕士)
|
||||
- [HatBoy](https://github.com/hatboy)
|
||||
|
||||
<!-- links -->
|
||||
|
||||
<!-- [linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=flat-square&logo=linkedin&colorB=555 -->
|
||||
|
||||
<!-- [linkedin-url]: https://linkedin.com/in/aJupyter -->
|
||||
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#SmartFlowAI/EmoLLM&Date)
|
||||
|
||||
## 🌟 Contributors
|
||||
|
||||
[](https://github.com/SmartFlowAI/EmoLLM/graphs/contributors)
|
||||
|
||||
[your-project-path]: SmartflowAI/EmoLLM
|
||||
[contributors-shield]: https://img.shields.io/github/contributors/SmartflowAI/EmoLLM.svg?style=flat-square
|
||||
[contributors-url]: https://github.com/SmartflowAI/EmoLLM/graphs/contributors
|
||||
[forks-shield]: https://img.shields.io/github/forks/SmartflowAI/EmoLLM.svg?style=flat-square
|
||||
[forks-url]: https://github.com/SmartflowAI/EmoLLM/network/members
|
||||
[stars-shield]: https://img.shields.io/github/stars/SmartflowAI/EmoLLM.svg?style=flat-square
|
||||
[stars-url]: https://github.com/SmartflowAI/EmoLLM/stargazers
|
||||
[issues-shield]: https://img.shields.io/github/issues/SmartflowAI/EmoLLM.svg?style=flat-square
|
||||
[issues-url]: https://img.shields.io/github/issues/SmartflowAI/EmoLLM.svg
|
||||
[license-shield]: https://img.shields.io/github/license/SmartflowAI/EmoLLM.svg?style=flat-square
|
||||
[license-url]: https://github.com/SmartFlowAI/EmoLLM/blob/main/LICENSE
|
||||
|
||||
[OpenXLab_App-image]: https://cdn-static.openxlab.org.cn/app-center/openxlab_app.svg
|
||||
[OpenXLab_Model-image]: https://cdn-static.openxlab.org.cn/header/openxlab_models.svg
|
||||
[OpenXLab_App-url]: https://openxlab.org.cn/apps/detail/Farewell1/EmoLLMV2.0
|
||||
[OpenXLab_Model-url]: https://openxlab.org.cn/models/detail/ajupyter/EmoLLM_internlm2_7b_full
|
||||
|
||||
## 交流群
|
||||
|
||||
- 如果失效,请移步Issue区
|
||||
|
||||
<p align="center">
|
||||
<img width="30%" src="https://github.com/SmartFlowAI/EmoLLM/assets/62385492/55ecd0aa-4832-4269-ad57-4c26f9aa286b" alt="EmoLLM官方交流群">
|
||||
</p>
|
||||
28
config.json
Normal file
28
config.json
Normal file
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"_name_or_path": "/root/model/LLM-Research/Meta-Llama-3-8B-Instruct",
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 128000,
|
||||
"eos_token_id": 128001,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 4096,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 14336,
|
||||
"max_position_embeddings": 8192,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 32,
|
||||
"num_key_value_heads": 8,
|
||||
"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-05,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 500000.0,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "float16",
|
||||
"transformers_version": "4.40.0",
|
||||
"use_cache": true,
|
||||
"vocab_size": 128256
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework":"Pytorch","task":"text-generation"}
|
||||
6
generation_config.json
Normal file
6
generation_config.json
Normal file
@@ -0,0 +1,6 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 128000,
|
||||
"eos_token_id": 128001,
|
||||
"transformers_version": "4.40.0"
|
||||
}
|
||||
3
pytorch_model-00001-of-00009.bin
Normal file
3
pytorch_model-00001-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:427a4ef75635f53a559b3cb1b380a7c7d154c037682410105cc4385c03793340
|
||||
size 1973460982
|
||||
3
pytorch_model-00002-of-00009.bin
Normal file
3
pytorch_model-00002-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:bdf620beb4ae359cf9b73f10cb5b9cedb1c68c33375ed36d653b5cc03eb3b0bd
|
||||
size 1895904598
|
||||
3
pytorch_model-00003-of-00009.bin
Normal file
3
pytorch_model-00003-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9f901a34cebc036e1f860bc8e9973e06118d6e0ac975675869937c1da9f7f312
|
||||
size 1979807738
|
||||
3
pytorch_model-00004-of-00009.bin
Normal file
3
pytorch_model-00004-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d1a88258445c370e23e901dd7acbe8db30e2f26a40f9460fe59fcf91aa8f298b
|
||||
size 1946237324
|
||||
3
pytorch_model-00005-of-00009.bin
Normal file
3
pytorch_model-00005-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:5df0a69d6341fe8b022d5c43abc48230ebe66502070545ec03fceea4155ce01e
|
||||
size 1979807802
|
||||
3
pytorch_model-00006-of-00009.bin
Normal file
3
pytorch_model-00006-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:261bc687793564e004fb7222adc2d064a4284284341e2ba89cefeacd8de36809
|
||||
size 1946237324
|
||||
3
pytorch_model-00007-of-00009.bin
Normal file
3
pytorch_model-00007-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:be7e251704f8500161b646df6cb615ae438a70dfd5764fd59db4e5535e0489af
|
||||
size 1979807802
|
||||
3
pytorch_model-00008-of-00009.bin
Normal file
3
pytorch_model-00008-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:798ac9adb92717228268320291bd9d953c1ef575f1887d09e4a1f78ebdb1363d
|
||||
size 1308690338
|
||||
3
pytorch_model-00009-of-00009.bin
Normal file
3
pytorch_model-00009-of-00009.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:5f93daece62cc7ae5f056ae49a22c87a252efaa11e7ac3f146d4ee52a39658bf
|
||||
size 1050674565
|
||||
3
pytorch_model.bin.index.json
Normal file
3
pytorch_model.bin.index.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:c6247fcb48ed7e0fb1f77e7b063aa45c92acba6847e09aeca7ce04a1cbe30e0f
|
||||
size 23950
|
||||
16
special_tokens_map.json
Normal file
16
special_tokens_map.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|end_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
410504
tokenizer.json
Normal file
410504
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
2062
tokenizer_config.json
Normal file
2062
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user