Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
multi-vector
feature-extraction
Generated from Trainer
dataset_size:640000
loss:Distillation
Eval Results (legacy)
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/ColBERT-Zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/ColBERT-Zero 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/ColBERT-Zero") 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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Update the Sentence Transformers section for the v6.0.1 prefix fix (#2)
- Update the Sentence Transformers section for the v6.0.1 prefix fix (947c08431adb8181d71bf33d00bedb54cd504bc6) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>43aefda
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Add Sentence Transformers usage (#1)
- Add Sentence Transformers usage (8a5d3e59378b168d2c97b5dbf1a8a9fd76340583) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>ce3db9d
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Update config_sentence_transformers.json
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Add new ColBERT model
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