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tiagozip
/
undyne

Token Classification
Transformers
ONNX
Safetensors
English
electra
question-answering
highlighting
distillation
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use tiagozip/undyne with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="tiagozip/undyne")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("tiagozip/undyne")
    model = AutoModelForTokenClassification.from_pretrained("tiagozip/undyne", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
undyne
123 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
tiagozip's picture
tiagozip
add widget examples
839c3d0 verified 15 days ago
  • onnx
    undyne: 13.5M answer-span highlighter distilled from an 82M teacher 15 days ago
  • .gitattributes
    1.52 kB
    initial commit 15 days ago
  • README.md
    3.46 kB
    add widget examples 15 days ago
  • config.json
    1.01 kB
    undyne: 13.5M answer-span highlighter distilled from an 82M teacher 15 days ago
  • example.py
    4.85 kB
    undyne: 13.5M answer-span highlighter distilled from an 82M teacher 15 days ago
  • model.safetensors
    54 MB
    xet
    undyne: 13.5M answer-span highlighter distilled from an 82M teacher 15 days ago
  • tokenizer.json
    711 kB
    undyne: 13.5M answer-span highlighter distilled from an 82M teacher 15 days ago
  • tokenizer_config.json
    351 Bytes
    undyne: 13.5M answer-span highlighter distilled from an 82M teacher 15 days ago