Sentence Similarity
Safetensors
sentence-transformers
English
PyLate
modernbert
ColBERT
embeddings
retrieval
feature-extraction
Generated from Trainer
dataset_size:1695819
loss:Contrastive
Eval Results (legacy)
text-embeddings-inference
🇪🇺 Region: EU
Instructions to use lightonai/ColBERT-Zero-supervised-noprompts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lightonai/ColBERT-Zero-supervised-noprompts 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-supervised-noprompts") queries_emb = model.encode(queries, is_query=True) docs_emb = model.encode(documents, is_query=False) - Notebooks
- Google Colab
- Kaggle
Download sentence_bert_config.json from lightonai/ColBERT-Zero-supervised-noprompts: direct link, hf CLI and curl.
- Browser
- Download file 57 Bytes
-
https://huggingface.co/lightonai/ColBERT-Zero-supervised-noprompts/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://lightonai/ColBERT-Zero-supervised-noprompts/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/lightonai/ColBERT-Zero-supervised-noprompts/resolve/main/sentence_bert_config.json
57 Bytes
| { | |
| "max_seq_length": 511, | |
| "do_lower_case": false | |
| } |