Nomic Embed: Training a Reproducible Long Context Text Embedder
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866917910686990336 |
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| author | Nussbaum, Zach Morris, John X. Duderstadt, Brandon Mulyar, Andriy |
| author_facet | Nussbaum, Zach Morris, John X. Duderstadt, Brandon Mulyar, Andriy |
| contents | 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 the short-context MTEB benchmark and the long context LoCo benchmark. We release the training code and model weights under an Apache 2.0 license. In contrast with other open-source models, we release the full curated training data and code that allows for full replication of nomic-embed-text-v1. You can find code and data to replicate the model at https://github.com/nomic-ai/contrastors. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_01613 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Nomic Embed: Training a Reproducible Long Context Text Embedder Nussbaum, Zach Morris, John X. Duderstadt, Brandon Mulyar, Andriy Computation and Language Artificial Intelligence 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 the short-context MTEB benchmark and the long context LoCo benchmark. We release the training code and model weights under an Apache 2.0 license. In contrast with other open-source models, we release the full curated training data and code that allows for full replication of nomic-embed-text-v1. You can find code and data to replicate the model at https://github.com/nomic-ai/contrastors. |
| title | Nomic Embed: Training a Reproducible Long Context Text Embedder |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2402.01613 |