Nomic Embed: Training a Reproducible Long Context Text Embedder
<|reference_start|>Nomic Embed: Training a Reproducible Long Context Text Embedder: 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 https://github.com/nomic-ai/contrastors<|reference_end|>
@article{nussbaum2024nomic,
    title={Nomic Embed: Training a Reproducible Long Context Text Embedder},
    author={Zach Nussbaum and John X. Morris and Brandon Duderstadt and Andriy
  Mulyar},
    journal={arXiv preprint arXiv:2402.01613},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.01613},
    primaryClass={cs.CL cs.AI}
}