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Fallovski
/
CrossencoderPharma

Text Ranking
sentence-transformers
Safetensors
roberta
cross-encoder
reranker
Generated from Trainer
dataset_size:11426
loss:BinaryCrossEntropyLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use Fallovski/CrossencoderPharma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Fallovski/CrossencoderPharma with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("Fallovski/CrossencoderPharma")
    
    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

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Preview of files found in this repository
  • .gitattributes
    1.52 kB
    initial commit 6 days ago
  • README.md
    20.3 kB
    Add new CrossEncoder model 6 days ago
  • config.json
    723 Bytes
    Add new CrossEncoder model 6 days ago
  • config_sentence_transformers.json
    262 Bytes
    Add new CrossEncoder model 6 days ago
  • model.safetensors
    445 MB
    xet
    Add new CrossEncoder model 6 days ago
  • modules.json
    131 Bytes
    Add new CrossEncoder model 6 days ago
  • sentence_bert_config.json
    225 Bytes
    Add new CrossEncoder model 6 days ago
  • special_tokens_map.json
    1.05 kB
    Add new CrossEncoder model 6 days ago
  • tokenizer.json
    4.49 MB
    Add new CrossEncoder model 6 days ago
  • tokenizer_config.json
    21.3 kB
    Add new CrossEncoder model 6 days ago