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figmtu
/
deberta-v3-aac-classifier

Text Classification
Transformers
Safetensors
English
deberta-v2
Model card Files Files and versions
xet
Community

Instructions to use figmtu/deberta-v3-aac-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use figmtu/deberta-v3-aac-classifier with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="figmtu/deberta-v3-aac-classifier")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("figmtu/deberta-v3-aac-classifier")
    model = AutoModelForSequenceClassification.from_pretrained("figmtu/deberta-v3-aac-classifier")
  • Notebooks
  • Google Colab
  • Kaggle
deberta-v3-aac-classifier
740 MB
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  • 2 contributors
History: 9 commits
kdv123's picture
kdv123
Update README.md
33e37e1 verified 13 days ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    652 Bytes
    Update README.md 13 days ago
  • added_tokens.json
    23 Bytes
    Upload tokenizer over 1 year ago
  • config.json
    1.01 kB
    Upload DebertaV2ForSequenceClassification over 1 year ago
  • model.safetensors
    738 MB
    xet
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  • special_tokens_map.json
    971 Bytes
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  • spm.model
    2.46 MB
    xet
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  • tokenizer_config.json
    1.26 kB
    Upload tokenizer over 1 year ago