H2O Open Ecosystem for State-of-the-art Large Language Models

Arno Candel, Jon McKinney, Philipp Singer, Pascal Pfeiffer, Maximilian Jeblick +2 more
10/17/2023
cs.CLcs.AI

No official code found. Best implementation: h2oai/h2ogpt (11,979 stars, Apache-2.0, last commit 2025-10-09). 1 more below.

Abstract

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 of diverse sizes. 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 fully open-source. We believe this work helps to boost AI development and make it more accessible, efficient and trustworthy. The demo is available at: https://gpt.h2o.ai/

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Code Implementations(2)

h2oai/h2ogptCommunity100%
Apache-2.0

Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/

11,9791,307TeX, HTMLMar 24, 20231 years agoApache-2.0
aichatgptembeddingsfedrampgenerative+9 more
h2oai/h2o-llmstudioCommunity100%
Apache-2.0

H2O LLM Studio - a framework and no-code GUI for fine-tuning LLMs. Documentation: https://docs.h2o.ai/h2o-llmstudio/

4,978532Shell, PythonApr 17, 20235 months agoApache-2.0
aichatbotchatgptfedrampfine-tuning+8 more

Cite this paper

@article{candel2023open,
  title  = {H2O Open Ecosystem for State-of-the-art Large Language Models},
  author = {Arno Candel and Jon McKinney and Philipp Singer and Pascal Pfeiffer and Maximilian Jeblick and Chun Ming Lee and Marcos V. Conde},
  year   = {2023},
  eprint = {2310.13012},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.13012v2}
}

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