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UVA-MSBA
/
ARISE-ADR-NLP

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

Instructions to use UVA-MSBA/ARISE-ADR-NLP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use UVA-MSBA/ARISE-ADR-NLP with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="UVA-MSBA/ARISE-ADR-NLP")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("UVA-MSBA/ARISE-ADR-NLP")
    model = AutoModelForSequenceClassification.from_pretrained("UVA-MSBA/ARISE-ADR-NLP")
  • Notebooks
  • Google Colab
  • Kaggle
ARISE-ADR-NLP
1.75 GB
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  • 1 contributor
History: 4 commits
xtinamall's picture
xtinamall
Upload DebertaV2ForSequenceClassification
7d0e1f5 verified 4 days ago
  • .gitattributes
    1.52 kB
    initial commit 9 days ago
  • README.md
    5.17 kB
    Upload tokenizer 9 days ago
  • added_tokens.json
    23 Bytes
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  • config.json
    846 Bytes
    Upload DebertaV2ForSequenceClassification 4 days ago
  • model.safetensors
    1.74 GB
    xet
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  • special_tokens_map.json
    286 Bytes
    Upload tokenizer 9 days ago
  • spm.model
    2.46 MB
    xet
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  • tokenizer.json
    8.66 MB
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  • tokenizer_config.json
    1.32 kB
    Upload tokenizer 9 days ago