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raphaelfontes
/
HealthNewsBRT

Text Classification
Transformers
PyTorch
Brazilian Sign Language
bert
news
health
classification
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use raphaelfontes/HealthNewsBRT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use raphaelfontes/HealthNewsBRT with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="raphaelfontes/HealthNewsBRT")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("raphaelfontes/HealthNewsBRT")
    model = AutoModelForSequenceClassification.from_pretrained("raphaelfontes/HealthNewsBRT", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle

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Preview of files found in this repository
  • .gitattributes
    1.52 kB
    initial commit almost 3 years ago
  • README.md
    3.29 kB
    Update README.md over 2 years ago
  • added_tokens.json
    3 Bytes
    upd: removido conteudo desnecessario almost 3 years ago
  • config.json
    935 Bytes
    upd: name_or_path config.json almost 3 years ago
  • pytorch_model.bin
    436 MB
    xet
    add: official trainer - 0.932565 almost 3 years ago
  • tokenizer.json
    678 kB
    add: tokenizer info almost 3 years ago
  • tokenizer_config.json
    2 Bytes
    Update tokenizer_config.json almost 3 years ago
  • trainer_state.json
    5.19 kB
    add: official trainer - 0.932565 almost 3 years ago
  • vocab.txt
    210 kB
    add: tokenizer info almost 3 years ago