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HarBat
/
distilled_bert_finetuning

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Model card Files Files and versions
xet
Metrics Training metrics Community
2

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

  • Libraries
  • Transformers

    How to use HarBat/distilled_bert_finetuning with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="HarBat/distilled_bert_finetuning")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("HarBat/distilled_bert_finetuning")
    model = AutoModelForSequenceClassification.from_pretrained("HarBat/distilled_bert_finetuning")
  • Notebooks
  • Google Colab
  • Kaggle
distilled_bert_finetuning
Ctrl+K
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  • 1 contributor
History: 21 commits
HarBat's picture
HarBat
Update README.md
28b7fe2 about 3 years ago
  • runs
    End of training over 3 years ago
  • .gitattributes
    1.38 kB
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  • .gitignore
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    Training in progress, epoch 1 over 3 years ago
  • README.md
    1.12 kB
    Update README.md about 3 years ago
  • config.json
    615 Bytes
    Training in progress, epoch 1 over 3 years ago
  • pytorch_model.bin
    268 MB
    xet
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
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  • tokenizer_config.json
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  • training_args.bin
    3.38 kB
    xet
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  • vocab.txt
    232 kB
    Training in progress, epoch 1 over 3 years ago