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temsa
/
OpenMed-mLiteClinical-IrishCorePII-135M-v1

Token Classification
Transformers
ONNX
Safetensors
English
Irish
distilbert
pii
de-identification
ireland
ppsn
eircode
finance
passport
phone-number
multilingual
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1")
    model = AutoModelForTokenClassification.from_pretrained("temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
OpenMed-mLiteClinical-IrishCorePII-135M-v1 / onnx
139 MB
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  • 1 contributor
History: 1 commit
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temsa
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  • config.json
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  • label_meta.json
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  • model_quantized.onnx
    135 MB
    xet
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  • onnx_export.json
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  • quantization.json
    163 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    2.92 MB
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  • tokenizer_config.json
    1.37 kB
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  • vocab.txt
    996 kB
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