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medspaner
/
mdeberta-v3-base-es-trials-attributes

Token Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
Model card Files Files and versions
xet
Community
1

Instructions to use medspaner/mdeberta-v3-base-es-trials-attributes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use medspaner/mdeberta-v3-base-es-trials-attributes with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="medspaner/mdeberta-v3-base-es-trials-attributes")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("medspaner/mdeberta-v3-base-es-trials-attributes")
    model = AutoModelForTokenClassification.from_pretrained("medspaner/mdeberta-v3-base-es-trials-attributes")
  • Notebooks
  • Google Colab
  • Kaggle
mdeberta-v3-base-es-trials-attributes
1.13 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
lcampillos's picture
lcampillos
Update README.md
ddad5f7 verified almost 2 years ago
  • .gitattributes
    1.57 kB
    Upload tokenizer.json over 2 years ago
  • README.md
    5.8 kB
    Update README.md almost 2 years ago
  • config.json
    1.4 kB
    Upload DebertaV2ForTokenClassification over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch.LongStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.FloatStorage"

    What is a pickle import?

    1.11 GB
    xet
    Upload DebertaV2ForTokenClassification over 2 years ago
  • tokenizer.json
    16.3 MB
    xet
    Upload tokenizer.json over 2 years ago