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ayushexel
/
ce-modernbert-trained-1epoch

Text Ranking
sentence-transformers
Safetensors
English
modernbert
cross-encoder
Generated from Trainer
dataset_size:2749365
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ayushexel/ce-modernbert-trained-1epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use ayushexel/ce-modernbert-trained-1epoch with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("ayushexel/ce-modernbert-trained-1epoch")
    
    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-modernbert-trained-1epoch
602 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
ayushexel's picture
ayushexel
Add new CrossEncoder model
5d691e4 verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    19.4 kB
    Add new CrossEncoder model about 1 year ago
  • config.json
    1.46 kB
    Add new CrossEncoder model about 1 year ago
  • model.safetensors
    598 MB
    xet
    Add new CrossEncoder model about 1 year ago
  • special_tokens_map.json
    694 Bytes
    Add new CrossEncoder model about 1 year ago
  • tokenizer.json
    3.58 MB
    Add new CrossEncoder model about 1 year ago
  • tokenizer_config.json
    21 kB
    Add new CrossEncoder model about 1 year ago