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leonweber
/
foo

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

Instructions to use leonweber/foo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use leonweber/foo with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="leonweber/foo")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("leonweber/foo")
    model = AutoModelForTokenClassification.from_pretrained("leonweber/foo")
  • Notebooks
  • Google Colab
  • Kaggle
foo
451 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
leonweber's picture
leonweber
add model
e986d21 almost 4 years ago
  • .gitattributes
    1.17 kB
    initial commit almost 4 years ago
  • config.json
    545 kB
    add model almost 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    449 MB
    xet
    add model almost 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer almost 4 years ago
  • tokenizer.json
    679 kB
    add tokenizer almost 4 years ago
  • tokenizer_config.json
    357 Bytes
    add tokenizer almost 4 years ago
  • vocab.txt
    225 kB
    add tokenizer almost 4 years ago