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NamanAgnih0tri
/
code-reranker-miniLM-staqc

Text Classification
sentence-transformers
Safetensors
bert
reranker
code search
cross-encoder
MiniLM
staqc
information retrieval
MRR
code understanding
python
stack-overflow
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use NamanAgnih0tri/code-reranker-miniLM-staqc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use NamanAgnih0tri/code-reranker-miniLM-staqc with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("NamanAgnih0tri/code-reranker-miniLM-staqc")
    
    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
code-reranker-miniLM-staqc
91.8 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
NamanAgnih0tri's picture
NamanAgnih0tri
Update README.md
9bcf5f1 verified 10 months ago
  • .gitattributes
    1.52 kB
    initial commit 10 months ago
  • README.md
    5.57 kB
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  • config.json
    852 Bytes
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  • model.safetensors
    90.9 MB
    xet
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  • readme.md
    5.85 kB
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  • special_tokens_map.json
    125 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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