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wandb
/
celadon

Text Classification
Transformers
Safetensors
multi-head-deberta-for-sequence-classification
custom_code
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use wandb/celadon with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="wandb/celadon", trust_remote_code=True)
    # Load model directly
    from transformers import AutoModelForSequenceClassification
    model = AutoModelForSequenceClassification.from_pretrained("wandb/celadon", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
celadon
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  • 1 contributor
History: 10 commits
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tcapelle
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932c0ff verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    366 Bytes
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  • added_tokens.json
    23 Bytes
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  • config.json
    1.14 kB
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  • configuration_deberta_multi.py
    273 Bytes
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  • model.safetensors
    565 MB
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  • modelling_deberta_multi.py
    1.15 kB
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  • special_tokens_map.json
    970 Bytes
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  • spm.model
    2.46 MB
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  • tokenizer.json
    8.66 MB
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  • tokenizer_config.json
    1.29 kB
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