1 code implementation • 27 Jul 2021 • Daniel D'souza, Zach Nussbaum, Chirag Agarwal, Sara Hooker
As machine learning models are increasingly employed to assist human decision-makers, it becomes critical to communicate the uncertainty associated with these model predictions.
1 code implementation • 6 Nov 2023 • Yuvanesh Anand, Zach Nussbaum, Adam Treat, Aaron Miller, Richard Guo, Ben Schmidt, GPT4All Community, Brandon Duderstadt, Andriy Mulyar
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.
1 code implementation • 2 Feb 2024 • Zach Nussbaum, John X. Morris, Brandon Duderstadt, Andriy Mulyar
This technical report describes the training of nomic-embed-text-v1, the first fully reproducible, open-source, open-weights, open-data, 8192 context length English text embedding model that outperforms both OpenAI Ada-002 and OpenAI text-embedding-3-small on short and long-context tasks.