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QuantaSparkLabs
/
ApexRetriever-Pro

Sentence Similarity
sentence-transformers
Safetensors
English
apex_retriever
rag
retrieval
semantic-search
faiss
bm25
reranker
cross-encoder
flan-t5
hybrid-search
dense-retrieval
ai
llm
search
question-answering
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use QuantaSparkLabs/ApexRetriever-Pro with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("QuantaSparkLabs/ApexRetriever-Pro")
    
    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-Pro / bi_encoder
135 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
    94.8 kB
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  • config.json
    661 Bytes
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  • config_sentence_transformers.json
    205 Bytes
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  • model.safetensors
    133 MB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    52 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.27 kB
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  • vocab.txt
    232 kB
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