GPT4All: An Ecosystem of Open Source Compressed Language Models
This work addresses accessibility issues for developers and researchers by providing open-source alternatives to costly and restricted LLMs, though it is incremental in building on existing model compression and open-source practices.
The paper tackles the problem of limited accessibility to large language models (LLMs) by introducing GPT4All, an open-source ecosystem that aims to democratize access to LLMs, evolving from a single model family into a comprehensive project.
Large language models (LLMs) have recently achieved human-level performance on a range of professional and academic benchmarks. The accessibility of these models has lagged behind their performance. State-of-the-art LLMs require costly infrastructure; are only accessible via rate-limited, geo-locked, and censored web interfaces; and lack publicly available code and technical reports. In this paper, we tell the story of GPT4All, a popular open source repository that aims to democratize access to LLMs. We outline the technical details of the original GPT4All model family, as well as the evolution of the GPT4All project from a single model into a fully fledged open source ecosystem. It is our hope that this paper acts as both a technical overview of the original GPT4All models as well as a case study on the subsequent growth of the GPT4All open source ecosystem.