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naver
/
v-splade-efficient

Feature Extraction
sentence-transformers
Safetensors
English
modernvbert
sparse-retrieval
splade
visual-document-retrieval
multimodal
information-retrieval
inference-free
sparse-encoder
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use naver/v-splade-efficient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use naver/v-splade-efficient with sentence-transformers:

    from sentence_transformers import SparseEncoder
    
    model = SparseEncoder("naver/v-splade-efficient", trust_remote_code=True)
    
    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
v-splade-efficient / query_0_VSPLADEStaticEmbedding
3.79 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
Tom Aarsen
Integrate with Sentence Transformers
b7875cd 3 months ago
  • config.json
    51 Bytes
    Integrate with Sentence Transformers 3 months ago
  • model.safetensors
    202 kB
    xet
    Integrate with Sentence Transformers 3 months ago
  • tokenizer.json
    3.59 MB
    Integrate with Sentence Transformers 3 months ago
  • tokenizer_config.json
    446 Bytes
    Integrate with Sentence Transformers 3 months ago