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Nargizi
/
screeve-postagger

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

Instructions to use Nargizi/screeve-postagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Nargizi/screeve-postagger with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="Nargizi/screeve-postagger")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Nargizi/screeve-postagger")
    model = AutoModelForTokenClassification.from_pretrained("Nargizi/screeve-postagger")
  • Notebooks
  • Google Colab
  • Kaggle
screeve-postagger
2.02 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 8 commits
Nargizi's picture
Nargizi
update model max length
11cd1dd over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    90 Bytes
    modify model card over 2 years ago
  • config.json
    945 Bytes
    update model over 2 years ago
  • generation_config.json
    161 Bytes
    upload model files over 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    1.73 MB
    xet
    update model over 2 years ago
  • special_tokens_map.json
    125 Bytes
    updated tokenizer with config over 2 years ago
  • tokenizer.json
    191 kB
    update tokenizer over 2 years ago
  • tokenizer_config.json
    382 Bytes
    update model max length over 2 years ago
  • vocab.txt
    99 kB
    updated tokenizer with config over 2 years ago