Sentence Similarity
Safetensors
sentence-transformers
PyLate
lfm2
liquid
edge
ColBERT
multi-vector
feature-extraction
Eval Results (legacy)
Instructions to use LiquidAI/LFM2-ColBERT-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use LiquidAI/LFM2-ColBERT-350M 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="LiquidAI/LFM2-ColBERT-350M") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
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README.md
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If you are interested in custom solutions with edge deployment, please contact [our sales team](https://www.liquid.ai/contact).
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```bibtex
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@misc{PyLate,
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If you are interested in custom solutions with edge deployment, please contact [our sales team](https://www.liquid.ai/contact).
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## Citation
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```
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@article{liquidai2025lfm2,
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title={LFM2 Technical Report},
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author={Liquid AI},
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journal={arXiv preprint arXiv:2511.23404},
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year={2025}
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}
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```
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```bibtex
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@misc{PyLate,
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