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ratish
/
DBERT_CleanDesc_MAKE_v10

Text Classification
Transformers
google-tensorflow TensorFlow
distilbert
generated_from_keras_callback
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use ratish/DBERT_CleanDesc_MAKE_v10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ratish/DBERT_CleanDesc_MAKE_v10 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="ratish/DBERT_CleanDesc_MAKE_v10")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("ratish/DBERT_CleanDesc_MAKE_v10")
    model = AutoModelForSequenceClassification.from_pretrained("ratish/DBERT_CleanDesc_MAKE_v10")
  • Notebooks
  • Google Colab
  • Kaggle
DBERT_CleanDesc_MAKE_v10
269 MB
Ctrl+K
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  • 1 contributor
History: 9 commits
ratish's picture
ratish
Training in progress epoch 9
be92a34 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    2.25 kB
    Training in progress epoch 9 about 3 years ago
  • config.json
    1.04 kB
    Training in progress epoch 0 about 3 years ago
  • special_tokens_map.json
    125 Bytes
    Training in progress epoch 0 about 3 years ago
  • tf_model.h5
    268 MB
    xet
    Training in progress epoch 9 about 3 years ago
  • tokenizer.json
    711 kB
    Training in progress epoch 0 about 3 years ago
  • tokenizer_config.json
    320 Bytes
    Training in progress epoch 0 about 3 years ago
  • vocab.txt
    232 kB
    Training in progress epoch 0 about 3 years ago