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syssec-utd
/
py313-pylingual-v1-segmenter

Token Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use syssec-utd/py313-pylingual-v1-segmenter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use syssec-utd/py313-pylingual-v1-segmenter with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="syssec-utd/py313-pylingual-v1-segmenter")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py313-pylingual-v1-segmenter")
    model = AutoModelForTokenClassification.from_pretrained("syssec-utd/py313-pylingual-v1-segmenter")
  • Notebooks
  • Google Colab
  • Kaggle
py313-pylingual-v1-segmenter / runs
7.13 kB
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  • 1 contributor
History: 3 commits
lc10934's picture
lc10934
Model save
b46f14c verified over 1 year ago
  • Feb07_03-37-28_tacosec0
    Model save over 1 year ago