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Mardiyyah
/
CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask

Token Classification
Transformers
Safetensors
English
bert
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask")
    model = AutoModelForTokenClassification.from_pretrained("Mardiyyah/CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
CeLLaTe-ner-2class-pubmedbert-tapt-combData-tokenizer-adapted-spanmask
443 MB
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  • 1 contributor
History: 2 commits
Mardiyyah's picture
Mardiyyah
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1bb5497 verified 14 days ago
  • .gitattributes
    1.52 kB
    initial commit 14 days ago
  • README.md
    2.81 kB
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  • added_tokens.json
    50.7 kB
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  • all_results.json
    545 Bytes
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  • config.json
    950 Bytes
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  • eval_results.json
    545 Bytes
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  • model.safetensors
    442 MB
    xet
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    1.08 MB
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  • tokenizer_config.json
    354 kB
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  • train_results.json
    234 Bytes
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  • trainer_state.json
    4.53 kB
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  • training_args.bin
    5.88 kB
    xet
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  • vocab.txt
    226 kB
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