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fastyBOOM
/
nerbert-recipe

Token Classification
Transformers
Safetensors
English
bert
ner
recipes
trained-from-scratch
Model card Files Files and versions
xet
Community

Instructions to use fastyBOOM/nerbert-recipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use fastyBOOM/nerbert-recipe with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="fastyBOOM/nerbert-recipe")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("fastyBOOM/nerbert-recipe")
    model = AutoModelForTokenClassification.from_pretrained("fastyBOOM/nerbert-recipe", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
nerbert-recipe
18.3 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
fastyBOOM's picture
fastyBOOM
Update README.md
ab960cb verified about 1 month ago
  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
    18 MB
    xet
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  • recipe_ner.ipynb
    212 kB
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  • tokenizer.json
    103 kB
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  • tokenizer_config.json
    329 Bytes
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