Text Classification
Transformers
Safetensors
Portuguese
deberta
fake-news
sequence-classification
portuguese
Eval Results (legacy)
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
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library_name: transformers
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# Model Card for Model ID
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library_name: transformers
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datasets:
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- HenriqueLz/fakerecogna2-extrativa-elections
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language:
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- pt
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metrics:
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- f1
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base_model:
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- PORTULAN/albertina-100m-portuguese-ptbr-encoder
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pipeline_tag: text-classification
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# Model Card for Model ID
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