Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
multi-vector
feature-extraction
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/LateOn-hpool-regularized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/LateOn-hpool-regularized 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-hpool-regularized") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Add ### PyLate section heading after the ST snippet
Browse files
README.md
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# tensor([[11.3723, 11.6385, 11.5022, 11.6186]])
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```
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First install PyLate:
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```bash
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# tensor([[11.3723, 11.6385, 11.5022, 11.6186]])
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```
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### PyLate
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First install PyLate:
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```bash
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