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sharkdodo
/
Indic-Bert-NER-Model

Token Classification
Transformers
Safetensors
English
albert
ner
named-entity-recognition
indic-languages
bert
medical-nlp
regulatory
pharmaceutical
Model card Files Files and versions
xet
Community

Instructions to use sharkdodo/Indic-Bert-NER-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sharkdodo/Indic-Bert-NER-Model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="sharkdodo/Indic-Bert-NER-Model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("sharkdodo/Indic-Bert-NER-Model")
    model = AutoModelForTokenClassification.from_pretrained("sharkdodo/Indic-Bert-NER-Model")
  • Notebooks
  • Google Colab
  • Kaggle
Indic-Bert-NER-Model
153 MB
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  • 1 contributor
History: 8 commits
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sharkdodo
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  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
    132 MB
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  • special_tokens_map.json
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  • spiece.model
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  • tokenizer.json
    15.3 MB
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  • tokenizer_config.json
    1.3 kB
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  • training_args.bin
    5.43 kB
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