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umarfarzan
/
clipworthy-deberta-model

Text Classification
Transformers
Safetensors
deberta-v2
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use umarfarzan/clipworthy-deberta-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use umarfarzan/clipworthy-deberta-model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="umarfarzan/clipworthy-deberta-model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("umarfarzan/clipworthy-deberta-model")
    model = AutoModelForSequenceClassification.from_pretrained("umarfarzan/clipworthy-deberta-model")
  • Notebooks
  • Google Colab
  • Kaggle
clipworthy-deberta-model
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  • 1 contributor
History: 3 commits
umarfarzan's picture
umarfarzan
Upload tokenizer
ae16d69 verified 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    5.17 kB
    Upload DebertaV2ForSequenceClassification 8 months ago
  • added_tokens.json
    23 Bytes
    Upload tokenizer 8 months ago
  • config.json
    886 Bytes
    Upload DebertaV2ForSequenceClassification 8 months ago
  • model.safetensors
    738 MB
    xet
    Upload DebertaV2ForSequenceClassification 8 months ago
  • special_tokens_map.json
    970 Bytes
    Upload tokenizer 8 months ago
  • tokenizer.json
    8.65 MB
    Upload tokenizer 8 months ago
  • tokenizer_config.json
    1.51 kB
    Upload tokenizer 8 months ago