h2oGPT: Democratizing Large Language Models
Summary
This paper introduces h2oGPT, a suite of open-source fine-tuned LLMs ranging from 7 to 40 billion parameters, designed as a truly open alternative to closed-source GPTs with 100% private document search capabilities.
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Paper page - h2oGPT: Democratizing Large Language Models
Source: https://huggingface.co/papers/2306.08161 Published on Jun 13, 2023
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Submitted byhttps://huggingface.co/akhaliq
AKon Jun 16, 2023
Abstract
h2oGPT provides open-source, fine-tuned LLMs based on Generative Pretrained Transformers with 100% private document search capabilities.
Foundation Large Language Models (LLMs) such as GPT-4 represent a revolution in AI due to their real-world applications though natural language processing. However, they also pose many significant risks such as the presence of biased, private, or harmful text, and the unauthorized inclusion of copyrighted material. We introduce h2oGPT, a suite of open-source code repositories for the creation and use of Large Language Models (LLMs) based on Generative Pretrained Transformers (GPTs). The goal of this project is to create the world’s best truly open-source alternative to closed-source GPTs. In collaboration with and as part of the incredible and unstoppable open-source community, we open-source several fine-tuned h2oGPT models from 7 to 40 Billion parameters, ready for commercial use under fully permissiveApache 2.0 licenses. Included in our release is 100%private document searchusing natural language. Open-source language models help boost AI development and make it more accessible and trustworthy. They lower entry hurdles, allowing people and groups to tailor these models to their needs. This openness increases innovation, transparency, and fairness. An open-source strategy is needed to share AI benefits fairly, and H2O.ai will continue to democratize AI andLLMs.
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