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yemen2016
/
nbbert_ED3

Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use yemen2016/nbbert_ED3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use yemen2016/nbbert_ED3 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="yemen2016/nbbert_ED3")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("yemen2016/nbbert_ED3")
    model = AutoModelForSequenceClassification.from_pretrained("yemen2016/nbbert_ED3", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
nbbert_ED3
715 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
yemen2016's picture
yemen2016
End of training
ac84eb3 verified almost 2 years ago
  • runs
    End of training almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    1.92 kB
    End of training almost 2 years ago
  • added_tokens.json
    31 Bytes
    Training in progress, epoch 1 almost 2 years ago
  • config.json
    922 Bytes
    Training in progress, epoch 1 almost 2 years ago
  • model.safetensors
    711 MB
    xet
    End of training almost 2 years ago
  • special_tokens_map.json
    310 Bytes
    Training in progress, epoch 1 almost 2 years ago
  • tokenizer.json
    2.92 MB
    Training in progress, epoch 1 almost 2 years ago
  • tokenizer_config.json
    1.51 kB
    Training in progress, epoch 1 almost 2 years ago
  • training_args.bin
    5.3 kB
    xet
    Training in progress, epoch 1 almost 2 years ago
  • vocab.txt
    996 kB
    Training in progress, epoch 1 almost 2 years ago