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tcepi
/
mbp_pas_model

Text Classification
Transformers
Safetensors
PyTorch
Portuguese
modernbert
binary-classification
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use tcepi/mbp_pas_model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="tcepi/mbp_pas_model")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("tcepi/mbp_pas_model")
    model = AutoModelForSequenceClassification.from_pretrained("tcepi/mbp_pas_model")
  • Notebooks
  • Google Colab
  • Kaggle
mbp_pas_model
602 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 7 commits
vic35get's picture
vic35get
Add classification report
b364f59 verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit 3 months ago
  • README.md
    3.5 kB
    Add detailed Model Card with metrics 3 months ago
  • classification_report.txt
    326 Bytes
    Add classification report 3 months ago
  • config.json
    2.09 kB
    Upload ModernBERT fine-tuned for binary classification 3 months ago
  • model.safetensors
    598 MB
    xet
    Upload ModernBERT fine-tuned for binary classification 3 months ago
  • test_results.json
    660 Bytes
    Add test results 3 months ago
  • tokenizer.json
    3.58 MB
    Upload tokenizer 3 months ago
  • tokenizer_config.json
    541 Bytes
    Upload tokenizer 3 months ago
  • train_results.json
    205 Bytes
    Add training results 3 months ago