Sentence Similarity
ONNX
Safetensors
sentence-transformers
PyLate
modernbert
ColBERT
multi-vector
feature-extraction
Generated from Trainer
dataset_size:640000
loss:Distillation
Eval Results (legacy)
text-embeddings-inference
Instructions to use lightonai/GTE-ModernColBERT-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/GTE-ModernColBERT-v1 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/GTE-ModernColBERT-v1") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Inference
- Notebooks
- Google Colab
- Kaggle
Download model.onnx from lightonai/GTE-ModernColBERT-v1: direct link, hf CLI and curl.
- Browser
- Download file 597 MB
-
https://huggingface.co/lightonai/GTE-ModernColBERT-v1/resolve/main/model.onnx
- Command line
-
hf download hf://lightonai/GTE-ModernColBERT-v1/model.onnx
-
curl -L -o model.onnx https://huggingface.co/lightonai/GTE-ModernColBERT-v1/resolve/main/model.onnx
597 MB
- Xet hash:
- 270c2fcac35941ae9cfaa0993482ac443e40bc9fc18c5e7f963488c3b1d867e7
- Size of remote file:
- 597 MB
- SHA256:
- a94c8e9a66f3d1954b88f28dacfb75b3457e6e5884c739b6c4b2a1009ad66d6c
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