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bozhou
/
DeBERTa-base

Image Feature Extraction
Transformers
PyTorch
deberta-v2
custom_code
Model card Files Files and versions
xet
Community

Instructions to use bozhou/DeBERTa-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bozhou/DeBERTa-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-feature-extraction", model="bozhou/DeBERTa-base", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("bozhou/DeBERTa-base", trust_remote_code=True)
    model = AutoModel.from_pretrained("bozhou/DeBERTa-base", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
DeBERTa-base
208 MB
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  • 3 contributors
History: 16 commits
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3v324v23
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  • modeling
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  • .gitattributes
    1.17 kB
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  • .gitignore
    1.78 kB
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  • README.md
    136 Bytes
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  • config.json
    927 Bytes
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  • model_config.json
    667 Bytes
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  • pytorch_model.bin
    207 MB
    xet
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  • tokenizer_config.json
    70 Bytes
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  • vocab.txt
    91.3 kB
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