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multifuly
/
certweb-reranker-model

Text Ranking
sentence-transformers
Safetensors
xlm-roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:7598
loss:BinaryCrossEntropyLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use multifuly/certweb-reranker-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use multifuly/certweb-reranker-model with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("multifuly/certweb-reranker-model")
    
    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
certweb-reranker-model
2.26 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
multifuly's picture
multifuly
Update tokenizer_config.json
825e05a verified 2 months ago
  • .gitattributes
    1.57 kB
    Upload 4 files 3 months ago
  • README.md
    26.8 kB
    Upload fine-tuned reranker model from Colab 2 months ago
  • config.json
    958 Bytes
    Upload fine-tuned reranker model from Colab 2 months ago
  • model.safetensors
    2.24 GB
    xet
    Upload fine-tuned reranker model from Colab 2 months ago
  • tokenizer.json
    17.1 MB
    xet
    Upload fine-tuned reranker model from Colab 2 months ago
  • tokenizer_config.json
    569 Bytes
    Update tokenizer_config.json 2 months ago