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liaad
/
srl-pt_mbert-base

Feature Extraction
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
multilingual
Portuguese
bert
bert-base-multilingual-cased
semantic role labeling
finetuned
Model card Files Files and versions
xet
Community
1

Instructions to use liaad/srl-pt_mbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use liaad/srl-pt_mbert-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="liaad/srl-pt_mbert-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("liaad/srl-pt_mbert-base")
    model = AutoModel.from_pretrained("liaad/srl-pt_mbert-base")
  • Notebooks
  • Google Colab
  • Kaggle
srl-pt_mbert-base
2.14 GB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 7 commits
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elishowk
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  • .gitattributes
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    allow flax about 5 years ago
  • README.md
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    Automatic correction of README.md metadata for keys. Contact website@huggingface.co for any question over 4 years ago
  • config.json
    1.42 kB
    Added model files. over 5 years ago
  • flax_model.msgpack
    711 MB
    xet
    upload flax model about 5 years ago
  • pytorch_model.bin
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  • special_tokens_map.json
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  • tf_model.h5
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  • tokenizer_config.json
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  • vocab.txt
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