EmoLLM
心理健康大模型、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2、LLama3.1
Stars: 757
EmoLLM is a series of large-scale psychological health counseling models that can support **understanding-supporting-helping users** in the psychological health counseling chain, which is fine-tuned from `LLM` instructions. Welcome everyone to star~⭐⭐. The currently open source `LLM` fine-tuning configurations are as follows:
README:
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:
欢迎大家为本项目做出贡献~
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:
- 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。
- 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。
- 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。
- 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。
- 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。
- 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。
- 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。
- 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。
- 【2024.09.14】基于Qwen2-7B-Instruct模型的Lora微调模型开源,微调配置文件地址:Qwen2-7B-Instruct_lora.py ,模型权重链接:ModelScope
- 【2024.08】基于GLM4-9B-chat微调Lora模型开源(基于LLaMA-Factory),详情见微调教程 ,模型权重链接:ModelScope
- 【2024.07.16】欢迎大家体验 EmoLLM V3.0 ,该模型是基于InternLM2.5-7B-Chat模型的全量微调,微调配置文件地址:internlm2_5_chat_7b_full.py ,模型权重链接:OpenXLab, ModelScope ,WebDemo地址: OpenXLab apps, 配套全量微调知乎教程。
- 【2024.07】欢迎大家使用稳定版 EmoLLM V2.0 进行日常使用和学术研究,模型权重链接:OpenXLab。
- 【2024.07】新增基于InternLM2_5_7B_chat微调配置、模型文件发布在 ModelScope。
- 【2024.06】新增基于LLaMA-FactoryGLM4-9B-chat微调指南、新增基于swift的微调指南、论文ESC-Eval: Evaluating Emotion Support Conversations in Large Language Models引用了EmoLLM且EmoLLM取得了较好的效果。
- 【2024.05.28】EmoLLM使用的多轮对话数据集CPsyCounD和专业评测方法已公开,详见2024 ACL findings《CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling》!
- 【2024.05.08】EmoLLM爹系男友阅览体验版上线 1. 百度AppBuilder 2. OpenXLab, 欢迎点赞收藏
- 【2024.05.07】增量预训练指南
- 【2024.05.04】基于LLaMA3_8b_instruct的EmoLLM3.0 OpenXLab Demo上线(重启链接), LLAMA3微调指南更新,在OpenXLab和ModelScope平台发布LLaMA3_8b_instruct-8B QLoRA微调模型 EmoLLM3.0权重
- 【2024.04.20】LLAMA3微调指南及基于LLaMA3_8b_instruct的艾薇开源
- 【2023.04.14】新增快速开始和保姆级教程BabyEmoLLM
- 【2024.04.02】在 Huggingface 上传老母亲心理咨询师
- 【2024.03.25】在百度飞桨平台发布爹系男友心理咨询师
- 【2024.03.24】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
- 【2024.03.12】在百度飞桨平台发布艾薇
- 【2024.03.11】 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,更新数据集统计及详细信息、路线图
- 【2024.03.09】 新增并发功能加速 QA 对生成、RAG pipeline
- 【2024.03.03】 基于InternLM2-7B-chat全量微调版本EmoLLM V2.0开源,需要两块A100*80G,更新专业评估,详见evaluate,更新基于PaddleOCR的PDF转txt工具脚本,详见scripts
查看更多
- 【2024.02.29】更新客观评估计算,详见evaluate,更新一系列数据集,详见datasets
- 【2024.02.27】更新英文readme和一系列数据集(舔狗和单轮对话)
- 【2024.02.23】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,配置文件,在线体验链接 - 【2024.02.23】更新若干微调配置,新增 data_pro.json(数量更多、场景更全、更丰富)和 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
- 【2024.02.18】 基于Qwen1_5-0_5B-Chat全量微调版本开源,算力有限的道友可以玩起来~
- 【2024.02.06】 EmoLLM在Openxlab 平台下载量高达18.7k,欢迎大家体验!
- 【2024.02.05】 项目荣获公众号NLP工程化推文宣传推文链接,为博主推广一波,欢迎大家关注!!🥳🥳
- 【2024.02.03】 项目宣传视频完成 😊
- 【2024.01.27】 完善数据构建文档、微调指南、部署指南、Readme等相关文档 👏
- 【2024.01.25】 EmoLLM V1.0 已部署上线 https://openxlab.org.cn/apps/detail/jujimeizuo/EmoLLM 😀
- 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
-
荣获AI 赋能大学计划“全国高校行”一等奖
-
🎉感谢以下媒体及公众号朋友对本项目的报道和支持(以下排名不分先后! 若有遗漏、十分抱歉, 一并感激! 欢迎补充!): NLP工程化, 机智流, 爱可可爱生活, 阿郎小哥, 大模型日知路, AI Code 等!
-
项目宣传视频 EmoLLM 已发布,欢迎大家围观 😀
- 硬件:A100 40G(仅针对InternLM2_7B_chat+qlora微调+deepspeed zero2优化)
- todo:发布更多硬件消耗细节
- Clone the repo
git clone https://github.com/SmartFlowAI/EmoLLM.git
- 请阅读快速体验查阅
- 快速上手:Baby EmoLLM
- 增量预训练详见增量预训练指南
- 【基于xtuner】全量、LoRA、QLoRA微调详见微调指南
- 【基于ms-swift】全量、LoRA、QLoRA微调详见微调指南
- 【基于LLaMA-Factory】全量、LoRA、QLoRA微调详见微调指南
- todo:待更新DPO训练
- 详见RAG
- 本模型评测分为通用评测和专业评测,请阅读评测指南查阅
更多详情
- xtuner:用于微调
- Transformers
- Pytorch
- LMDeploy:用于量化部署
- Stremlit:用于构建Demo
- DeepSpeed:并行训练
- LLaMA-Factory:训练框架
- ms-swift:训练框架
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。
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
用户名 | 学校/组织 | 备注 | 贡献 |
---|---|---|---|
aJupyter | 南开大学在读硕士 | DataWhale成员 | 项目发起人 |
MING-ZCH | 华中科技大学在读本科生 | LLM x Mental health 研究者 | 项目联合负责人 |
chg0901 | 韩国光云大学在读博士 MiniSora | DataWhale意向成员 DataWhale鲸英助教团成员 | 项目联合负责人 |
jujimeizuo | 江南大学在读硕士 | ||
Smiling-Weeping-zhr | 哈尔滨工业大学(威海)在读本科生 | ||
8baby8 | 飞桨领航团区域主管 | 文心大模型核心开发者 | |
zxazys | 南开大学在读硕士 | ||
JasonLLLLLLLLLLL | swufe | ||
MrCatAI | AI搬用工 | ||
ZeyuBa | 自动化所在读硕士 | ||
aiyinyuedejustin | 宾夕法尼亚大学在读硕士 | ||
Nobody-ML | 中国石油大学(华东)在读本科生 | ||
Mxoder | 北京航空航天大学在读本科生 | ||
Anooyman | 南京理工大学硕士 | ||
Vicky-3021 | 西安电子科技大学硕士(研0) | ||
SantiagoTOP | 太原理工大学在读硕士 | 数据清洗,文档管理、Baby EmoLLM维护 | |
zealot52099 | 个人开发者 | 清洗数据、LLM微调、RAG | |
wwwyfff | 复旦大学在读硕士 | ||
Yicooong | 南开大学在读硕士 | ||
jkhumor | 南开大学在读硕士 | RAG | |
lll997150986 | 南开大学在读硕士 | 微调 | |
nln-maker | 南开大学在读硕士 | 前后端开发 | |
dream00001 | 南开大学在读硕士 | 前后端开发 | |
王几行XING | 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 | |
TingWei | 电子科技大学硕士毕业 | 微信公众号:AI大模型在手 | 微调 |
PengYu | 石河子大学在读硕士 | LLM微调 |
该项目签署了 MIT 授权许可,详情请参阅 LICENSE
如果本项目对您的工作有所帮助,请使用以下格式引用:
@misc{EmoLLM,
title={EmoLLM},
author={EmoLLM},
url={https://github.com/SmartFlowAI/EmoLLM/},
year={2024}
}
- 如果失效,请移步Issue区
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for EmoLLM
Similar Open Source Tools
EmoLLM
EmoLLM is a series of large-scale psychological health counseling models that can support **understanding-supporting-helping users** in the psychological health counseling chain, which is fine-tuned from `LLM` instructions. Welcome everyone to star~⭐⭐. The currently open source `LLM` fine-tuning configurations are as follows:
TigerBot
TigerBot is a cutting-edge foundation for your very own LLM, providing a world-class large model for innovative Chinese-style contributions. It offers various upgrades and features, such as search mode enhancements, support for large context lengths, and the ability to play text-based games. TigerBot is suitable for prompt-based game engine development, interactive game design, and real-time feedback for playable games.
awesome-ai-painting
This repository, named 'awesome-ai-painting', is a comprehensive collection of resources related to AI painting. It is curated by a user named 秋风, who is an AI painting enthusiast with a background in the AIGC industry. The repository aims to help more people learn AI painting and also documents the user's goal of creating 100 AI products, with current progress at 4/100. The repository includes information on various AI painting products, tutorials, tools, and models, providing a valuable resource for individuals interested in AI painting and related technologies.
Firefly
Firefly is an open-source large model training project that supports pre-training, fine-tuning, and DPO of mainstream large models. It includes models like Llama3, Gemma, Qwen1.5, MiniCPM, Llama, InternLM, Baichuan, ChatGLM, Yi, Deepseek, Qwen, Orion, Ziya, Xverse, Mistral, Mixtral-8x7B, Zephyr, Vicuna, Bloom, etc. The project supports full-parameter training, LoRA, QLoRA efficient training, and various tasks such as pre-training, SFT, and DPO. Suitable for users with limited training resources, QLoRA is recommended for fine-tuning instructions. The project has achieved good results on the Open LLM Leaderboard with QLoRA training process validation. The latest version has significant updates and adaptations for different chat model templates.
widgets
Widgets is a desktop component front-end open source component. The project is still being continuously improved. The desktop component client can be downloaded and run in two ways: 1. https://www.microsoft.com/store/productId/9NPR50GQ7T53 2. https://widgetjs.cn After cloning the code, you need to download the dependency in the project directory: `shell pnpm install` and run: `shell pnpm serve`
Semi-Auto-NovelAI-to-Pixiv
Semi-Auto-NovelAI-to-Pixiv is a powerful tool that enables batch image generation with NovelAI, along with various other useful features in a super user-friendly interface. It allows users to create images, generate random images, upload images to Pixiv, apply filters, enhance images, add watermarks, and more. The tool also supports video-to-image conversion and various image manipulation tasks. It offers a seamless experience for users looking to automate image processing tasks.
Llama-Chinese
Llama中文社区是一个专注于Llama模型在中文方面的优化和上层建设的高级技术社区。 **已经基于大规模中文数据,从预训练开始对Llama2模型进行中文能力的持续迭代升级【Done】**。**正在对Llama3模型进行中文能力的持续迭代升级【Doing】** 我们热忱欢迎对大模型LLM充满热情的开发者和研究者加入我们的行列。
Qbot
Qbot is an AI-oriented automated quantitative investment platform that supports diverse machine learning modeling paradigms, including supervised learning, market dynamics modeling, and reinforcement learning. It provides a full closed-loop process from data acquisition, strategy development, backtesting, simulation trading to live trading. The platform emphasizes AI strategies such as machine learning, reinforcement learning, and deep learning, combined with multi-factor models to enhance returns. Users with some Python knowledge and trading experience can easily utilize the platform to address trading pain points and gaps in the market.
chatluna
Chatluna is a machine learning model plugin that provides chat services with large language models. It is highly extensible, supports multiple output formats, and offers features like custom conversation presets, rate limiting, and context awareness. Users can deploy Chatluna under Koishi without additional configuration. The plugin supports various models/platforms like OpenAI, Azure OpenAI, Google Gemini, and more. It also provides preset customization using YAML files and allows for easy forking and development within Koishi projects. However, the project lacks web UI, HTTP server, and project documentation, inviting contributions from the community.
haystack-core-integrations
This repository contains integrations to extend the capabilities of Haystack version 2.0 and onwards. The code in this repo is maintained by deepset, see each integration's `README` file for details around installation, usage and support.
llm-book
The 'llm-book' repository is dedicated to the introduction of large-scale language models, focusing on natural language processing tasks. The code is designed to run on Google Colaboratory and utilizes datasets and models available on the Hugging Face Hub. Note that as of July 28, 2023, there are issues with the MARC-ja dataset links, but an alternative notebook using the WRIME Japanese sentiment analysis dataset has been added. The repository covers various chapters on topics such as Transformers, fine-tuning language models, entity recognition, summarization, document embedding, question answering, and more.
For similar tasks
EmoLLM
EmoLLM is a series of large-scale psychological health counseling models that can support **understanding-supporting-helping users** in the psychological health counseling chain, which is fine-tuned from `LLM` instructions. Welcome everyone to star~⭐⭐. The currently open source `LLM` fine-tuning configurations are as follows:
For similar jobs
EmoLLM
EmoLLM is a series of large-scale psychological health counseling models that can support **understanding-supporting-helping users** in the psychological health counseling chain, which is fine-tuned from `LLM` instructions. Welcome everyone to star~⭐⭐. The currently open source `LLM` fine-tuning configurations are as follows:
MindChat
MindChat is a psychological large language model designed to help individuals relieve psychological stress and solve mental confusion, ultimately improving mental health. It aims to provide a relaxed and open conversation environment for users to build trust and understanding. MindChat offers privacy, warmth, safety, timely, and convenient conversation settings to help users overcome difficulties and challenges, achieve self-growth, and development. The tool is suitable for both work and personal life scenarios, providing comprehensive psychological support and therapeutic assistance to users while strictly protecting user privacy. It combines psychological knowledge with artificial intelligence technology to contribute to a healthier, more inclusive, and equal society.
PsyDI
PsyDI is a multi-modal and interactive chatbot designed for psychological assessments. It aims to explore users' cognitive styles through interactive analysis of their inputs, ultimately determining their Myers-Briggs Type Indicator (MBTI). The chatbot offers customized feedback and detailed analysis for each user, with upcoming features such as an MBTI gallery. Users can access PsyDI directly online to begin their journey of self-discovery.
awesome-llm-role-playing-with-persona
Awesome-llm-role-playing-with-persona is a curated list of resources for large language models for role-playing with assigned personas. It includes papers and resources related to persona-based dialogue systems, personalized response generation, psychology of LLMs, biases in LLMs, and more. The repository aims to provide a comprehensive collection of research papers and tools for exploring role-playing abilities of large language models in various contexts.
devil.ai_public
Devil.ai is a repository containing logic and data files for determining personality results. It includes classes for extended logic and calculation data related to MBTI personality types. The repository is licensed under MIT.
aides-jeunes
The user interface (and the main server) of the simulator of aids and social benefits for young people. It is based on the free socio-fiscal simulator Openfisca.
MISSING-PERSONS-DATABASE-2024-KENYA-FINANCE-BILL-PROTESTS-
The Missing Persons 2024 Antifinance Bill Demonstrations Kenya database is an AI-powered platform designed to track and identify individuals who have gone missing during the ongoing protests. It aims to assist in reuniting families by providing a centralized online resource for all Kenyans. The platform allows for crowdsourced information upload, monitoring disappearances, and tracking unidentified bodies to create a comprehensive database. Key features include a user-friendly interface, AI-powered search, real-time updates, secure handling of data, and detailed reporting.