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rcds
/
MiniLM-swiss_citation_extraction-de-fr-it

Token Classification
Transformers
PyTorch
Safetensors
German
French
Italian
bert
Model card Files Files and versions
xet
Community
2

Instructions to use rcds/MiniLM-swiss_citation_extraction-de-fr-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use rcds/MiniLM-swiss_citation_extraction-de-fr-it with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="rcds/MiniLM-swiss_citation_extraction-de-fr-it")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("rcds/MiniLM-swiss_citation_extraction-de-fr-it")
    model = AutoModelForTokenClassification.from_pretrained("rcds/MiniLM-swiss_citation_extraction-de-fr-it", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
MiniLM-swiss_citation_extraction-de-fr-it
1.59 GB
Ctrl+K
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  • 2 contributors
History: 11 commits
kapllan's picture
kapllan
Update README.md
45068a8 about 3 years ago
  • .gitattributes
    1.66 kB
    First commit (#1) about 3 years ago
  • README.md
    4.51 kB
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  • all_results.json
    4.98 kB
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  • config.json
    965 Bytes
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  • model.safetensors
    235 MB
    xet
    Adding `safetensors` variant of this model (#2) about 3 years ago
  • predict_results.json
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  • pytorch_model.bin
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  • sentencepiece.bpe.model
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  • special_tokens_map.json
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  • test_predictions_detailed.csv
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  • tokenizer.json
    17.1 MB
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  • tokenizer_config.json
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  • train_results.json
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  • trainer_state.json
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  • training_args.bin
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    xet
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