Add a technical paper with link in model card (#1)
Browse files- Add a technical paper with link in model card (9f32d3bfbad0574d676e0eb08cb997f9fa7482c6)
Co-authored-by: Mengyao Xu <[email protected]>
README.md
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The **nvidia/llama-nemoretriever-colembed-3b-v1** is a late interaction embedding model fine-tuned for query-document retrieval. Users can input `queries`, which are text, or `documents` which are page images, to the model. The model outputs ColBERT-style multi-vector numerical representations for input queries and documents. It achieved 1st place on ViDoRe V1 (nDCG@5), ViDoRe V2 (nDCG@5) and MTEB VisualDocumentRetrieval (Rank Borda) (as of 27th June, 2025).
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This model is for non-commercial/research use only.
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### License/Terms of Use
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The **nvidia/llama-nemoretriever-colembed-3b-v1** is a late interaction embedding model fine-tuned for query-document retrieval. Users can input `queries`, which are text, or `documents` which are page images, to the model. The model outputs ColBERT-style multi-vector numerical representations for input queries and documents. It achieved 1st place on ViDoRe V1 (nDCG@5), ViDoRe V2 (nDCG@5) and MTEB VisualDocumentRetrieval (Rank Borda) (as of 27th June, 2025).
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For more technical details, please refer to our technical report: [Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model](https://www.arxiv.org/abs/2507.05513)
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This model is for non-commercial/research use only.
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### License/Terms of Use
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