# h2oGPT: Democratizing Large Language Models

**Authors:** Arno Candel, Jon McKinney, Philipp Singer, Pascal Pfeiffer, Maximilian Jeblick, Prithvi Prabhu, Jeff Gambera, Mark Landry, Shivam Bansal, Ryan Chesler, Chun Ming Lee, Marcos V. Conde, Pasha Stetsenko, Olivier Grellier, SriSatish Ambati  
**arXiv:** [2306.08161](https://arxiv.org/abs/2306.08161)  
**Date:** 2023-06-13  
**Summary page:** https://www.summarizepaper.com/en/paper/2306.08161v2/

## Key points

- H2O.ai is committed to democratizing AI and LLMs through the h2oGPT project
- h2oGPT aims to create open-source code repositories for Large Language Models (LLMs) based on Generative Pretrained Transformers (GPTs)
- The models range from 7 to 40 Billion parameters and are ready for commercial use under Apache 2.0 licenses
- The release includes a feature of 100% private document search using natural language
- Lowering entry barriers allows individuals and groups to tailor the models to their specific needs, fostering innovation, transparency, and fairness
- H2O.ai actively engages with the open-source community and recognizes the importance of sharing AI benefits fairly
- The authors behind this project work at H2O.ai Inc., indicating ongoing work by the organization

## Summary

H2O.ai is committed to democratizing AI and LLMs through the groundbreaking project h2oGPT. It aims to create open-source code repositories for the development and use of Large Language Models (LLMs) based on Generative Pretrained Transformers (GPTs). These models range from 7 to 40 Billion parameters and are fine-tuned and ready for commercial use under fully permissive Apache 2.0 licenses. The release includes an impressive feature of 100% private document search using natural language. By lowering entry barriers, individuals and groups can tailor these models to their specific needs, fostering innovation, transparency, and fairness while mitigating risks associated with biased or harmful content. H2O.ai recognizes the importance of sharing AI benefits fairly through an open-source strategy and actively engages with the unstoppable open-source community. With h2oGPT's contribution to the field, AI becomes more inclusive and empowers users to harness its potential. The authors behind this project include Arno Candel, Jon McKinney, Philipp Singer, Pascal Pfeiffer, Maximilian Jeblick, Prithvi Prabhu, Jeff Gambera, Mark Landry, Shivam Bansal, Ryan Chesler, Chun Ming Lee Marcos V. Conde Pasha Stetsenko Olivier Grellier SriSatish Ambati who collectively work at H2O.ai Inc., indicating that this is an ongoing work by the organization.