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Computer Science > Computation and Language

arXiv:2402.01613 (cs)
[Submitted on 2 Feb 2024]

Title:Nomic Embed: Training a Reproducible Long Context Text Embedder

Authors:Zach Nussbaum, John X. Morris, Brandon Duderstadt, Andriy Mulyar
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Abstract: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. We release the training code and model weights under an Apache 2 license. In contrast with other open-source models, we release a training data loader with 235 million curated text pairs that allows for the full replication of nomic-embed-text-v1. You can find code and data to replicate the model at this https URL
Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2402.01613 [cs.CL]
  (or arXiv:2402.01613v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2402.01613

Submission history

From: Andriy Mulyar [view email]
[v1] Fri, 2 Feb 2024 18:23:18 UTC (3,769 KB)
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