README_EN.md

EmoLLM - Large Languge Model for Mental Health

EmoLLM

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EmoLLM is a series of large language models designed to understand, support and help customers in mental health counseling. It is fine-tuned from the LLM instructions. We really appreciate it if you can give it a star~⭐⭐. The open-sourced configuration is as follows:

model	type
InternLM2_7B_chat	qlora
InternLM2_7B_chat	full finetuning
InternLM2_1_8B_chat	full finetuning
Qwen_7b_chat	qlora
Qwen1_5-0_5B-Chat	full finetuning
Baichuan2_13B_chat	qlora
ChatGLM3_6B	lora
DeepSeek MoE_16B_chat	qlora
Mixtral 8x7B_instruct	qlora
……	……
Everyone is welcome to contribute to this project ~

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The Model is aimed at fully understanding and promoting the mental health of individuals, groups, and society. This model typically includes the following key components:

• Cognitive factors: Involving an individual's thought patterns, belief systems, cognitive biases, and problem-solving abilities. Cognitive factors significantly impact mental health as they affect how individuals interpret and respond to life events.
• Emotional factors: Including emotion regulation, emotional expression, and emotional experiences. Emotional health is a crucial part of mental health, involving how individuals manage and express their emotions and how they recover from negative emotions.
• Behavioral factors: Concerning an individual's behavior patterns, habits, and coping strategies. This includes stress management skills, social skills, and self-efficacy, which is the confidence in one's abilities.
• Social environment: Comprising external factors such as family, work, community, and cultural background, which have direct and indirect impacts on an individual's mental health.
• Physical health: There is a close relationship between physical and mental health. Good physical health can promote mental health and vice versa.
• Psychological resilience: Refers to an individual's ability to recover from adversity and adapt. Those with strong psychological resilience can bounce back from challenges and learn and grow from them.
• Prevention and intervention measures: The Mental Health Grand Model also includes strategies for preventing psychological issues and promoting mental health, such as psychological education, counseling, therapy, and social support systems.
• Assessment and diagnostic tools: Effective promotion of mental health requires scientific tools to assess individuals' psychological states and diagnose potential psychological issues.

Recent Updates

• 【2024.3.3】 Based on InternLM2-7B-chat full amount of fine-tuned version of open source, need two A100*80G, update professional evaluation, see evaluate, update PaddleOCR-based PDF to txt tool scripts, see scripts.

• 【2024.2.29】 Updated objective assessment calculations, see evaluate for details. A series of datasets have also been updated, see datasets for details.

• 【2024.2.27】 Updated English README and a series of datasets (licking dogs and one-round dialogue)

• 【2024.2.23】The "Gentle Lady Psychologist Ai Wei" based on InternLM2_7B_chat_qlora was launched. Click here to obtain the model weights, configuration file, online experience link

• 【2024.2.23】Updated several fine-tuning configurations, added data_pro.json (more quantity, more comprehensive scenarios, richer content) and aiwei.json (dedicated to the gentle lady role-play, featuring Emoji expressions), the "Gentle Lady Psychologist Ai Wei" is coming soon.

• 【2024.2.18】 The full fine-tuned version based on Qwen1_5-0_5B-Chat has been open-sourced. Friends with limited computational resources can now dive in and explore it.

View More

• 【2024.2.6】 Open-sourced based on the Qwen1_5-0_5B-Chat full-scale fine-tuned version, friends with limited computing power can start experimenting~

• 【2024.2.5】 The project has been promoted by the official WeChat account NLP Engineering. Here's the link to the article. Welcome everyone to follow!! 🥳🥳

• 【2024.2.3】 Project Vedio at bilibili 😊
• 【2024.1.27】 Complete data construction documentation, fine-tuning guide, deployment guide, Readme, and other related documents 👏
• 【2024.1.25】 Complete the first version of EmoLLM and deploy it online https://openxlab.org.cn/apps/detail/jujimeizuo/EmoLLM 😀

Roadmap

Contents

• EmoLLM - Large Languge Model for Mental Health
  • Everyone is welcome to contribute to this project ~
    • Recent Updates
  • Contents - Pre-development Configuration Requirements. - User Guide
    • File Directory Explanation
    • Data Construction
    • Fine-tuning Guide
    • Deployment Guide
    • Frameworks Used
      • How to participate in this project
    • Version control
    • Authors (in no particular order)
    • Copyright Notice
    • Acknowledgments
  • Star History
  • 🌟 Contributors

Pre-development Configuration Requirements.

• A100 40G (specifically for InternLM2_7B_chat + qlora fine-tuning + deepspeed zero2 optimization)

User Guide

1. Clone the repo

git clone https://github.com/SmartFlowAI/EmoLLM.git

1. Read in sequence or read sections you're interested in：
   • File Directory Explanation
   • Data Construction
   • Fine-tuning Guide
   • Deployment Guide
   • View More Details

File Directory Explanation

├─assets：Image Resources
├─datasets：Dataset
├─demo：demo scripts
├─generate_data：Data Generation Guide
│  └─xinghuo
├─scripts：Some Available Tools
└─xtuner_config：Fine-tuning Guide
    └─images

Data Construction

Please read the Data Construction Guide for reference.

The dataset used for this fine-tuning can be found at datasets

Fine-tuning Guide

For details, see the fine-tuning guide

Deployment Guide

For details, see the deployment guide

Additional Details

Frameworks Used

• Xtuner
• Transformers
• Pytorch
• …

How to participate in this project

Contributions make the open-source community an excellent place for learning, inspiration, and creation. Any contribution you make is greatly appreciated.

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

Version control

This project uses Git for version control. You can see the current available versions in the repository.

Authors (in no particular order)

aJupyter@Datawhale member, Master's student at Nankai University

jujimeizuo@Master's student at Jiangnan University

Smiling&Weeping@Undergraduate student at Harbin Institute of Technology (Weihai)

Farewell@

ZhouXinAo@Master's student at Nankai University

MING_X @Undergraduate at Huazhong University of Science and Technology

Z_L@swufe

MrCatAI@AI Removal of Labour

ZeyuBa@Master's student at Institute of Automation

aiyinyuedejustin@Master's student at University of Pennsylvania

Nobody-ML@Undergraduate at China University of Petroleum (East China)

chg0901@PhD Candidate at Kwangwoon University

Copyright Notice

The project is licensed under the MIT License. Please refer to the details LICENSE

Acknowledgments

• Sanbu
• Shanghai Artificial Intelligence Laboratory
• Vanin
• Bloom up (WeChat Official Account Promotion)

Star History

🌟 Contributors

Communication group

• If it fails, go to the Issue section.