Sentence Similarity
ONNX
Safetensors
sentence-transformers
PyLate
modernbert
ColBERT
feature-extraction
multilingual
code search
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/mLateOn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/mLateOn 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/mLateOn") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53a4479c7ceaaaca701335375279aec5354f76298aa1fa7a07d824f9c9ceb7e1
- Size of remote file:
- 34.4 MB
- SHA256:
- 33b6ce1724e107a3298219a322b4c963fcfcb9c8661bd1f30189bdd0d36c4669
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.