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Muzian
/
minimind-rerank-moe

Text Ranking
sentence-transformers
Safetensors
Chinese
English
minimind
cross-encoder
reranker
rerank
chinese
Mixture of Experts
qwen3-reranker
Model card Files Files and versions
xet
Community

Instructions to use Muzian/minimind-rerank-moe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Muzian/minimind-rerank-moe with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Muzian/minimind-rerank-moe")
    
    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
minimind-rerank-moe
408 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
Muzian's picture
Muzian
Add model card: Dense vs MoE comparison + counterintuitive finding
39a4a4f verified 12 days ago
  • images
    Upload images/banner.png with huggingface_hub 12 days ago
  • .gitattributes
    1.64 kB
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  • README.md
    2.94 kB
    Add model card: Dense vs MoE comparison + counterintuitive finding 12 days ago
  • config.json
    635 Bytes
    Upload folder using huggingface_hub 12 days ago
  • model.safetensors
    407 MB
    xet
    Upload folder using huggingface_hub 12 days ago
  • tokenizer.json
    482 kB
    Upload folder using huggingface_hub 12 days ago
  • tokenizer_config.json
    13.6 kB
    Upload folder using huggingface_hub 12 days ago