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samagra14wefi
/
PreferED

Text Classification
Keras
PyTorch
English
deberta-v2
evaluations
Model card Files Files and versions
xet
Community

Instructions to use samagra14wefi/PreferED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Keras

    How to use samagra14wefi/PreferED with Keras:

    # Available backend options are: "jax", "torch", "tensorflow".
    import os
    os.environ["KERAS_BACKEND"] = "jax"
    
    import keras
    
    model = keras.saving.load_model("hf://samagra14wefi/PreferED")
    
  • Notebooks
  • Google Colab
  • Kaggle
PreferED
1.75 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 12 commits
samagra14wefi's picture
samagra14wefi
Update README.md
c1bd7b1 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    6.29 kB
    Update README.md over 2 years ago
  • config.json
    990 Bytes
    Upload DebertaV2ForSequenceClassification over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2"

    What is a pickle import?

    1.74 GB
    xet
    Upload DebertaV2ForSequenceClassification over 2 years ago
  • special_tokens_map.json
    173 Bytes
    Upload tokenizer over 2 years ago
  • tokenizer.json
    8.65 MB
    Upload tokenizer over 2 years ago
  • tokenizer_config.json
    520 Bytes
    Upload tokenizer over 2 years ago