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skfrost19
/
reranker-MiniLM-L12-H384-uncased-msmarco-bce

Text Ranking
sentence-transformers
Safetensors
English
bert
cross-encoder
Generated from Trainer
dataset_size:1990000
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use skfrost19/reranker-MiniLM-L12-H384-uncased-msmarco-bce with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use skfrost19/reranker-MiniLM-L12-H384-uncased-msmarco-bce with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("skfrost19/reranker-MiniLM-L12-H384-uncased-msmarco-bce")
    
    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
reranker-MiniLM-L12-H384-uncased-msmarco-bce
1.52 kB
Ctrl+K
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  • 1 contributor
History: 1 commit
skfrost19's picture
skfrost19
initial commit
fed5b1e verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago