#ChatGLM-6B

The LangChain-ChatGLM-Webui project provides a WebUI utilizing LangChain and ChatGLM-6B series models for applications grounded in local knowledge. Supporting multiple text file formats like txt, docx, md, and pdf, it includes models such as ChatGLM-6B and Belle for enhanced embedding functionalities. Designed for real-world AI model implementation, the project offers online accessibility through HuggingFace, ModelScope, and AIStudio. Compatible with Python 3.8.1+, it facilitates straightforward deployment. Continuous updates and community engagement ensure its dynamic advancement, inviting developer participation without exaggerated claims.

Explore a bilingual conversational AI model designed for deployment on consumer-grade hardware. Featuring 62 billion parameters and utilizing INT4 quantization, it allows local deployment with as little as 6GB memory. Tailored for Chinese question-answering, the model is enhanced through extensive bilingual training and reinforcement learning. The project supports academic research with open access to its weights and offers customization options for developers. Importantly, it stresses responsible use by encouraging compliance with open-source licenses and ethical standards.

The project implements advanced fine-tuning techniques for the ChatGLM-6B model, including LoRA, P-Tuning V2, and Reinforcement Learning with Human Feedback (RLHF). It features a comprehensive Web UI for single GPU-based training, evaluation, and inference, highlighting its role in optimizing large language models. The repository supports various datasets like Stanford Alpaca, BELLE, and GPT-4 generated data, enhancing ChatGLM's adaptability to diverse datasets and tuning methods. Although the project is no longer actively maintained, it has significantly contributed to the efficient tuning of language models.