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HMC83
/
name-detector-32m

Token Classification
Transformers
ONNX
Safetensors
English
modernbert
pii
redaction
person-names
ner
ettin
distillation
Model card Files Files and versions
xet

Instructions to use HMC83/name-detector-32m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use HMC83/name-detector-32m with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="HMC83/name-detector-32m")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("HMC83/name-detector-32m")
    model = AutoModelForTokenClassification.from_pretrained("HMC83/name-detector-32m", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
name-detector-32m / code
11.2 kB
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  • 1 contributor
History: 1 commit
HMC83's picture
HMC83
Add the model, its run-time code and the model card
e75778c verified 3 days ago
  • decode.py
    3.18 kB
    Add the model, its run-time code and the model card 3 days ago
  • rules.py
    4.86 kB
    Add the model, its run-time code and the model card 3 days ago
  • runtime.py
    3.18 kB
    Add the model, its run-time code and the model card 3 days ago