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HenriqueLz
/
albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections

Text Classification
Transformers
Safetensors
Portuguese
deberta
fake-news
sequence-classification
portuguese
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections")
    model = AutoModelForSequenceClassification.from_pretrained("HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections
557 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 6 commits
HenriqueLz's picture
HenriqueLz
docs: harmonize canonical layout, exact F1 metric, hardware details and verified citations
0e21d54 verified about 2 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.22 kB
    docs: harmonize canonical layout, exact F1 metric, hardware details and verified citations about 2 months ago
  • config.json
    920 Bytes
    Upload DebertaForSequenceClassification about 1 year ago
  • model.safetensors
    557 MB
    xet
    Upload DebertaForSequenceClassification about 1 year ago