Sentence Similarity
ONNX
Safetensors
sentence-transformers
English
code
PyLate
modernbert
ColBERT
multi-vector
feature-extraction
Generated from Trainer
dataset_size:2117771
loss:Contrastive
embeddings
retrieval
code search
Eval Results (legacy)
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/LateOn-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/LateOn-Code 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-Code") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 46b27f638f4f670f22a737d34357175ab2f58e4dbb9523f9b4d19e1a7989f97c
- Size of remote file:
- 150 MB
- SHA256:
- a62a88b4e3ebb76e8bc5f0263d17b773c667d27bc73c5120e3131048dd1554ef
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