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haejiness
/
tmp-ner

Token Classification
Transformers
PyTorch
roberta
Model card Files Files and versions
xet
Community
1

Instructions to use haejiness/tmp-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use haejiness/tmp-ner with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="haejiness/tmp-ner")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("haejiness/tmp-ner")
    model = AutoModelForTokenClassification.from_pretrained("haejiness/tmp-ner")
  • Notebooks
  • Google Colab
  • Kaggle
tmp-ner
388 MB
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  • 1 contributor
History: 2 commits
haejiness's picture
haejiness
Upload RobertaForTokenClassification
e745d1a verified over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.17 kB
    Upload RobertaForTokenClassification over 1 year ago
  • config.json
    1.03 kB
    Upload RobertaForTokenClassification over 1 year ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    388 MB
    xet
    Upload RobertaForTokenClassification over 1 year ago