Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
feature-extraction
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/LateOn-unsupervised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/LateOn-unsupervised with sentence-transformers:
from pylate import models queries = [ "Which planet is known as the Red Planet?", "What is the largest planet in our solar system?", ] documents = [ ["Mars is the Red Planet.", "Venus is Earth's twin."], ["Jupiter is the largest planet.", "Saturn has rings."], ] model = models.ColBERT(model_name_or_path="lightonai/LateOn-unsupervised") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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### BibTeX
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<!--
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## Glossary
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### BibTeX
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```bibtex
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@misc{sourty2025denseonlateon,
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title={DenseOn and LateOn: State-of-the-Art LightOn Retrieval Models},
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author={Sourty, Rapha{\"e}l and Chaffin, Antoine and Weller, Orion and Demoura, Paulo and Chatelain, Amelie},
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year={2026},
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howpublished={\url{https://huggingface.co/blog/lightonai/denseon-lateon}},
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}
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```
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```bibtex
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@inproceedings{DBLP:conf/cikm/ChaffinS25,
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author = {Antoine Chaffin and
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Rapha{\"{e}}l Sourty},
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editor = {Meeyoung Cha and
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Chanyoung Park and
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Noseong Park and
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Carl Yang and
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Senjuti Basu Roy and
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Jessie Li and
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Jaap Kamps and
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Kijung Shin and
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Bryan Hooi and
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Lifang He},
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title = {PyLate: Flexible Training and Retrieval for Late Interaction Models},
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booktitle = {Proceedings of the 34th {ACM} International Conference on Information
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and Knowledge Management, {CIKM} 2025, Seoul, Republic of Korea, November
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10-14, 2025},
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pages = {6334--6339},
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publisher = {{ACM}},
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year = {2025},
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url = {https://github.com/lightonai/pylate},
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doi = {10.1145/3746252.3761608},
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}
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```
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<!--
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## Glossary
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