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tcepi
/
helbert-prunned

Fill-Mask
Transformers
Safetensors
Portuguese
bert
feature-extraction
legal
licitação
editais
Model card Files Files and versions
xet
Community

Instructions to use tcepi/helbert-prunned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use tcepi/helbert-prunned with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="tcepi/helbert-prunned")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("tcepi/helbert-prunned")
    model = AutoModel.from_pretrained("tcepi/helbert-prunned")
  • Notebooks
  • Google Colab
  • Kaggle
helbert-prunned
277 MB
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  • 1 contributor
History: 5 commits
vic35get's picture
vic35get
Update README.md
9bd1f31 verified 12 days ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    5.27 kB
    Update README.md 12 days ago
  • added_tokens.json
    191 Bytes
    Upload tokenizer over 1 year ago
  • config.json
    843 Bytes
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  • model.safetensors
    275 MB
    xet
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    799 kB
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  • tokenizer_config.json
    3.44 kB
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  • vocab.txt
    277 kB
    Upload tokenizer over 1 year ago