HuggingFaceFW/fineweb
FineWeb is a dataset of over 15 trillion tokens of cleaned and deduplicated English web data from CommonCrawl. It is optimized for LLM performance and processed using the datatrove library. The dataset aims to provide high-quality data for training large language models and outperforms other commonly used web datasets.We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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FineWeb is a large-scale dataset designed to provide high-quality web data for training large language models. It includes over 15 trillion tokens of cleaned and deduplicated English web data from CommonCrawl. The dataset is processed using the datatrove library and is optimized for LLM performance. It outperforms other commonly used web datasets in benchmark tasks.
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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
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.
SoulChat2.0: Psychological Counselor's Digital Twin Framework
SoulChat2.0 is a framework for constructing the digital twin of psychological counselors, designed to support the development of AI applications in mental health. It includes a data generation module and a modeling module, enabling the creation of personalized counseling models based on limited real-world counseling cases.