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antoinelouis
/
colbert-xm

Sentence Similarity
Safetensors
sentence-transformers
colbert-ai
xmod
colbert
multi-vector
passage-retrieval
Eval Results (legacy)
Model card Files Files and versions
xet
Community
5

Instructions to use antoinelouis/colbert-xm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use antoinelouis/colbert-xm with sentence-transformers:

    from sentence_transformers import MultiVectorEncoder
    
    model = MultiVectorEncoder("antoinelouis/colbert-xm")
    
    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
colbert-xm
3.43 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 19 commits
antoinelouis's picture
antoinelouis
tomaarsen's picture
tomaarsen HF Staff
Add Sentence Transformers usage (#5)
4390256 about 2 months ago
  • .gitattributes
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  • README.md
    21.3 kB
    Add Sentence Transformers usage (#5) about 2 months ago
  • artifact.metadata
    2.14 kB
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  • config.json
    1.92 kB
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  • custom.py
    6.59 kB
    Create custom.py over 2 years ago
  • model.safetensors
    3.41 GB
    xet
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
    1.18 kB
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