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ajax-law
/
cross-encoder-binary-classification-base

Text Classification
Transformers
Safetensors
roberta
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ajax-law/cross-encoder-binary-classification-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ajax-law/cross-encoder-binary-classification-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ajax-law/cross-encoder-binary-classification-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("ajax-law/cross-encoder-binary-classification-base")
    model = AutoModelForSequenceClassification.from_pretrained("ajax-law/cross-encoder-binary-classification-base")
  • Notebooks
  • Google Colab
  • Kaggle
cross-encoder-binary-classification-base
502 MB
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  • 1 contributor
History: 3 commits
asw97's picture
asw97
Upload tokenizer
82307cf over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • config.json
    818 Bytes
    Accuracy: 0.0000, Epoch: 0, Steps: -1 over 2 years ago
  • merges.txt
    456 kB
    Upload tokenizer over 2 years ago
  • model.safetensors
    499 MB
    xet
    Accuracy: 0.0000, Epoch: 0, Steps: -1 over 2 years ago
  • special_tokens_map.json
    957 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    2.11 MB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    1.25 kB
    Upload tokenizer over 2 years ago
  • vocab.json
    798 kB
    Upload tokenizer over 2 years ago