H2O Open Ecosystem for State-of-the-art Large Language Models
Authors: name: Arno Candel, name: Jon McKinney, name: Philipp Singer, name: Pascal Pfeiffer, name: Maximilian Jeblick, name: Chun Ming Lee, name: Marcos V. Conde

Large Language Models (LLMs) represent a revolution in AI. However, they also
pose many significant risks, such as the presence of biased, private,
copyrighted or harmful text. For this reason we need open, transparent and safe
solutions. We introduce a complete open-source ecosystem for developing and
testing LLMs. The goal of this project is to boost open alternatives to
closed-source approaches. We release h2oGPT, a family of fine-tuned LLMs from 7
to 70 Billion parameters. We also introduce H2O LLM Studio, a framework and
no-code GUI designed for efficient fine-tuning, evaluation, and deployment of
LLMs using the most recent state-of-the-art techniques. Our code and models are
licensed under fully permissive Apache 2.0 licenses. We believe open-source
language models help to boost AI development and make it more accessible and
trustworthy. The demo is available at: https://gpt.h2o.ai/