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enricollen
/
ItColBERT

Sentence Similarity
Safetensors
sentence-transformers
Italian
pylate
modernbert
colbert
late-interaction
italian
retrieval
information-retrieval
rag
multi-vector
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use enricollen/ItColBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use enricollen/ItColBERT with sentence-transformers:

    from sentence_transformers import MultiVectorEncoder
    
    model = MultiVectorEncoder("enricollen/ItColBERT")
    
    queries = ["Which planet is known as the Red Planet?"]
    documents = [
    	"Venus is often called Earth's twin because of its similar size and proximity.",
    	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
    	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
    ]
    
    query_embeddings = model.encode_query(queries)
    document_embeddings = model.encode_document(documents)
    
    similarities = model.similarity(query_embeddings, document_embeddings)
    print(similarities)
  • Notebooks
  • Google Colab
  • Kaggle
ItColBERT / 1_Dense
393 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
enricollen's picture
enricollen
Add new ColBERT model
6bd0ed7 verified 2 months ago
  • config.json
    160 Bytes
    Add new ColBERT model 2 months ago
  • model.safetensors
    393 kB
    xet
    Add new ColBERT model 2 months ago