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chinilla
/
ProBERT-1.0

Text Classification
Transformers
Safetensors
English
distilbert
rhetorical-confidence
behavioral-stability
type-i-ghost-detection
ai-safety
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use chinilla/ProBERT-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use chinilla/ProBERT-1.0 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="chinilla/ProBERT-1.0")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("chinilla/ProBERT-1.0")
    model = AutoModelForSequenceClassification.from_pretrained("chinilla/ProBERT-1.0", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ProBERT-1.0
269 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 12 commits
chinilla's picture
chinilla
Update README.md
cfbfba8 verified about 1 month ago
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  • NOTICE
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  • QUICKSTART.md
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  • README.md
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  • eval_calibration.py
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  • probert_training_20260131_004706.csv
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  • tokenizer_config.json
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