title: H2O Open Ecosystem for State-of-the-art Large Language Models
summary: 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/
paper_authors._id: 6535d963b3852ed1ceeff1c6
paper_authors.name: Arno Candel
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-23T09:43:39.227Z
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paper_authors.fullname: Arno Candel
paper_authors.type: user
paper_authors.user: arnocandel
paper_authors._id: 6535d963b3852ed1ceeff1c7
paper_authors.name: Jon McKinney
paper_authors._id: 6535d963b3852ed1ceeff1c8
paper_authors.name: Philipp Singer
paper_authors.status: admin_assigned
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paper_authors.fullname: Philipp Singer
paper_authors.type: user
paper_authors.user: psinger
paper_authors._id: 6535d963b3852ed1ceeff1c9
paper_authors.name: Pascal Pfeiffer
paper_authors.status: admin_assigned
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paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1676417502037-6316fc44c92fd6fee3161e9a.png
paper_authors.fullname: Pascal Pfeiffer
paper_authors.type: user
paper_authors.user: ilu000
paper_authors._id: 6535d963b3852ed1ceeff1ca
paper_authors.name: Maximilian Jeblick
paper_authors.status: admin_assigned
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paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1674725099569-614c9145b44c102499783617.jpeg
paper_authors.fullname: Maximilian Jeblick
paper_authors.type: user
paper_authors.user: MaxJeblick
paper_authors._id: 6535d963b3852ed1ceeff1cb
paper_authors.name: Chun Ming Lee
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-23T09:44:27.144Z
paper_authors._id: 623aa9d00351d42298c4e930
paper_authors.avatarUrl: /avatars/137d5698d8bfac2d8a4175e892d7c206.svg
paper_authors.fullname: Chun Ming Lee
paper_authors.type: user
paper_authors.user: leecming
paper_authors._id: 6535d963b3852ed1ceeff1cc
paper_authors.name: Marcos V. Conde
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-23T09:44:32.826Z
paper_authors._id: 634169d1a7582111c3f46bae
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/634169d1a7582111c3f46bae/xEYokhORHsSqpMBZTJWJ7.jpeg
paper_authors.fullname: Marcos V. Conde
paper_authors.type: user
paper_authors.user: marcosv
paper_title: H2O Open Ecosystem for State-of-the-art Large Language Models
paper_summary: 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/
paper_ai_summary: An open-source ecosystem is introduced for developing and testing Large Language Models (LLMs), including a family of fine-tuned models and a GUI for efficient use of state-of-the-art techniques.
paper_ai_keywords: Large Language Models LLMs fine-tuned parameter-efficient fine-tuning