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texturejc
/
texture-frames-de-args

Token Classification
Transformers
German
frame-semantics
framenet
salsa
german
semantic-parsing
srl
argument-extraction
Model card Files Files and versions
xet
Community

Instructions to use texturejc/texture-frames-de-args with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use texturejc/texture-frames-de-args with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="texturejc/texture-frames-de-args")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("texturejc/texture-frames-de-args", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
texture-frames-de-args
1.36 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
texturejc's picture
texturejc
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  • .gitattributes
    1.52 kB
    initial commit 8 days ago
  • README.md
    4.42 kB
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  • added_tokens.json
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  • args2_model.pt

    Detected Pickle imports (3)

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

    What is a pickle import?

    1.36 GB
    xet
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  • role2id.json
    17.1 kB
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  • special_tokens_map.json
    437 Bytes
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  • tokenizer.json
    730 kB
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  • tokenizer_config.json
    1.69 kB
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  • vocab.txt
    240 kB
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