HeartLink - Empathetic Psychological Model
HeartLink is an empathetic psychological model that uses a large language model fine-tuned on a large empathetic Q&A dataset. It can perceive users' emotions and experiences during conversations and provide empathetic responses using rich psychological knowledge, aiming to understand, comfort, and support users. The responses include emoji expressions to bridge the gap with users, offering psychological support and help during consultations.
Detailed Introduction
The HeartLink project is based on the InternLM2-Chat model and has been fine-tuned to achieve empathetic functionality. The project supports text-to-speech synthesis and digital human display, and provides user emotion chart analysis. The project is under continuous development, and contributions through Star, PR, and Issue are welcome. The HeartLink psychological empathy question-and-answer dataset is derived from real psychological counseling scenarios. The first version uses about 180k rounds of question-and-answer pairs. The data covers a wide range of scenarios, including love, marriage, workplace, life, society, learning, sex, past, emotions, education, counseling, crisis, and many other rich scenarios.
MoreDataset
SmartFlowAI/EmoLLM: Psychology LLM、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2
Psychology LLM、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2 - SmartFlowAI/EmoLLM
Mental-Health-Corpus-github
The Mental Health Corpus contains labeled comments on mental health issues, used for sentiment and toxic language analysis.
Hugging Face Dataset - NamelessAI Helply
This paper discusses Helply - a synthesized ML training dataset focused on psychology and therapy, created by Alex Scott and published by NamelessAI. The dataset developed by Alex Scott is a comprehensive collection of synthesized data designed to train LLMs in understanding psychological and therapeutic contexts. This dataset aims to simulate real-world interactions between therapists and patients, enabling ML models to learn from a wide range of scenarios and therapeutic techniques.