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KRLabsOrg
/
acl-verbatim-modernbert

Token Classification
Transformers
Safetensors
English
modernbert
semantic-highlighting
extractive-qa
evidence-selection
acl-anthology
custom_code
Model card Files Files and versions
xet
Community

Instructions to use KRLabsOrg/acl-verbatim-modernbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use KRLabsOrg/acl-verbatim-modernbert with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="KRLabsOrg/acl-verbatim-modernbert", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("KRLabsOrg/acl-verbatim-modernbert", trust_remote_code=True)
    model = AutoModelForTokenClassification.from_pretrained("KRLabsOrg/acl-verbatim-modernbert", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
acl-verbatim-modernbert
602 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
adaamko's picture
adaamko
Update README.md
6b6059d verified about 11 hours ago
  • .gitattributes
    1.52 kB
    initial commit 18 days ago
  • README.md
    8.39 kB
    Update README.md about 11 hours ago
  • config.json
    1.5 kB
    Upload folder using huggingface_hub 18 days ago
  • model.safetensors
    598 MB
    xet
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  • modeling_acl_verbatim.py
    4.43 kB
    Upload folder using huggingface_hub 18 days ago
  • special_tokens_map.json
    694 Bytes
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  • tokenizer.json
    3.58 MB
    Upload folder using huggingface_hub 18 days ago
  • tokenizer_config.json
    21 kB
    Upload folder using huggingface_hub 18 days ago