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ALJIACHI
/
Mizan-Rerank-v3-Turbo

Text Ranking
sentence-transformers
Safetensors
Arabic
modernbert
cross-encoder
reranker
arabic
long-context
rag
islamic
distilled
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use ALJIACHI/Mizan-Rerank-v3-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ALJIACHI/Mizan-Rerank-v3-Turbo with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("ALJIACHI/Mizan-Rerank-v3-Turbo")
    
    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
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Thank you for the Mizan rerankers — excited to try V3-Turbo!

1
#1 opened 18 days ago by
ZenoAbderrahim
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