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QuantaSparkLabs
/
ApexRetriever

Sentence Similarity
sentence-transformers
Safetensors
English
apex_retriever
rag
retrieval
semantic-search
faiss
bm25
cross-encoder
hybrid-search
dense-retrieval
ai
search
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use QuantaSparkLabs/ApexRetriever with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("QuantaSparkLabs/ApexRetriever")
    
    query = "Which planet is known as the Red Planet?"
    passages = [
    	"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.",
    	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
    ]
    
    scores = model.predict([(query, passage) for passage in passages])
    print(scores)
  • Notebooks
  • Google Colab
  • Kaggle
ApexRetriever / bi_encoder
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
QuantaSparkLabs's picture
QuantaSparkLabs
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  • 1_Pooling
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  • README.md
    94.6 kB
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  • config.json
    823 Bytes
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  • config_sentence_transformers.json
    282 Bytes
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  • model.safetensors
    438 MB
    xet
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    414 Bytes
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