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lucasflins
/
CE-MiniLM-L3-H384-uncased-RankNet-20260207-052807

Text Ranking
sentence-transformers
Safetensors
bert
cross-encoder
reranker
Generated from Trainer
dataset_size:164849
loss:RankNetLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use lucasflins/CE-MiniLM-L3-H384-uncased-RankNet-20260207-052807 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use lucasflins/CE-MiniLM-L3-H384-uncased-RankNet-20260207-052807 with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("lucasflins/CE-MiniLM-L3-H384-uncased-RankNet-20260207-052807")
    
    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
CE-MiniLM-L3-H384-uncased-RankNet-20260207-052807
1.52 kB
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  • 1 contributor
History: 1 commit
lucasflins's picture
lucasflins
initial commit
75ae74e verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago