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oeg
/
software_benchmark_multidomain

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

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

  • Libraries
  • Transformers

    How to use oeg/software_benchmark_multidomain with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="oeg/software_benchmark_multidomain")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("oeg/software_benchmark_multidomain")
    model = AutoModelForTokenClassification.from_pretrained("oeg/software_benchmark_multidomain")
  • Notebooks
  • Google Colab
  • Kaggle
software_benchmark_multidomain
438 MB
Ctrl+K
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  • 1 contributor
History: 7 commits
esgg's picture
esgg
Update README.md
96a557c over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
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  • config.json
    913 Bytes
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  • pytorch_model.bin
    437 MB
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    717 kB
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  • tokenizer_config.json
    465 Bytes
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  • training_args.bin
    3.96 kB
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  • vocab.txt
    228 kB
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