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yjoonjang
/
reviewsearch-sparse

Feature Extraction
sentence-transformers
Safetensors
sparse-encoder
sparse
asymmetric
inference-free
splade
Generated from Trainer
dataset_size:46954
loss:CachedSpladeLoss
loss:SparseMultipleNegativesRankingLoss
loss:FlopsLoss
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use yjoonjang/reviewsearch-sparse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use yjoonjang/reviewsearch-sparse with sentence-transformers:

    from sentence_transformers import SparseEncoder
    
    model = SparseEncoder("yjoonjang/reviewsearch-sparse")
    
    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
reviewsearch-sparse / query_0_SparseStaticEmbedding
834 kB
Ctrl+K
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  • 1 contributor
History: 1 commit
yjoonjang's picture
yjoonjang
learned-sparse retriever (SPLADE doc-v3-gte S1)
97c1846 verified 4 months ago
  • config.json
    23 Bytes
    learned-sparse retriever (SPLADE doc-v3-gte S1) 4 months ago
  • model.safetensors
    122 kB
    xet
    learned-sparse retriever (SPLADE doc-v3-gte S1) 4 months ago
  • tokenizer.json
    712 kB
    learned-sparse retriever (SPLADE doc-v3-gte S1) 4 months ago
  • tokenizer_config.json
    590 Bytes
    learned-sparse retriever (SPLADE doc-v3-gte S1) 4 months ago