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BrundageLab
/
SpotRemover-bioclinicalbert-baseline

Token Classification
Transformers
Safetensors
bert
Model card Files Files and versions
xet
Community

Instructions to use BrundageLab/SpotRemover-bioclinicalbert-baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BrundageLab/SpotRemover-bioclinicalbert-baseline with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="BrundageLab/SpotRemover-bioclinicalbert-baseline")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("BrundageLab/SpotRemover-bioclinicalbert-baseline")
    model = AutoModelForTokenClassification.from_pretrained("BrundageLab/SpotRemover-bioclinicalbert-baseline")
  • Notebooks
  • Google Colab
  • Kaggle
SpotRemover-bioclinicalbert-baseline
432 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 4 commits
BrundageLab's picture
BrundageLab
Upload best checkpoint: Best performing ClinicalBert model (90% synth) for veterinary de-ID.
09baaa3 verified 5 months ago
  • .gitattributes
    1.52 kB
    initial commit 5 months ago
  • README.md
    5.17 kB
    Upload best checkpoint: Baseline BioClinicalBERT model (90% synth). 5 months ago
  • config.json
    1.01 kB
    Upload best checkpoint: Best performing ClinicalBert model (90% synth) for veterinary de-ID. 5 months ago
  • model.safetensors
    431 MB
    xet
    Upload best checkpoint: Best performing ClinicalBert model (90% synth) for veterinary de-ID. 5 months ago
  • special_tokens_map.json
    695 Bytes
    Upload tokenizer 5 months ago
  • tokenizer.json
    669 kB
    Upload tokenizer 5 months ago
  • tokenizer_config.json
    1.3 kB
    Upload tokenizer 5 months ago
  • vocab.txt
    213 kB
    Upload tokenizer 5 months ago