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webis
/
tiny-bert-ranker

Text Ranking
sentence-transformers
Safetensors
English
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
2

Instructions to use webis/tiny-bert-ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use webis/tiny-bert-ranker with sentence-transformers:

    from sentence_transformers import CrossEncoder
    
    model = CrossEncoder("webis/tiny-bert-ranker")
    
    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
tiny-bert-ranker
Ctrl+K
Ctrl+K
  • 4 contributors
History: 4 commits
mam10eks's picture
mam10eks
tomaarsen's picture
tomaarsen HF Staff
Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers` (#2)
f99bd25 verified 11 months ago
  • .gitattributes
    1.57 kB
    initial commit almost 2 years ago
  • README.md
    1.14 kB
    Update model metadata to set pipeline tag to the new `text-ranking` and library name to `sentence-transformers` (#2) 11 months ago
  • config.json
    877 Bytes
    initial commit almost 2 years ago
  • model.safetensors
    17.5 MB
    xet
    initial commit almost 2 years ago
  • special_tokens_map.json
    695 Bytes
    initial commit almost 2 years ago
  • tokenizer.json
    712 kB
    initial commit almost 2 years ago
  • tokenizer_config.json
    1.38 kB
    initial commit almost 2 years ago
  • vocab.txt
    232 kB
    initial commit almost 2 years ago