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
Commit History
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Add Sentence Transformers usage (#8)
- Add Sentence Transformers usage (388eb6b05f318f5924f70f3ab39db69c69af4ed2) - Add ### PyLate section heading after the ST snippet (96aadae01ced098370daf77b5d4a6ddd0bfd622c) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>9d727d7
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Add new_version pointer to LFM2.5-ColBERT-350M (#7)
- Add new_version pointer to LFM2.5-ColBERT-350M (b5f649b421c6f8ffbc9dc887581de81c0af7a1a9) Co-authored-by: Daniel van Strien <davanstrien@users.noreply.huggingface.co>6d3e56d
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