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SOTAagi2030
/
PocketIntent-Pilot

Text Classification
Transformers
Safetensors
bert
mobile
Model card Files Files and versions
xet
Community

Instructions to use SOTAagi2030/PocketIntent-Pilot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use SOTAagi2030/PocketIntent-Pilot with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="SOTAagi2030/PocketIntent-Pilot")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("SOTAagi2030/PocketIntent-Pilot")
    model = AutoModelForSequenceClassification.from_pretrained("SOTAagi2030/PocketIntent-Pilot", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
PocketIntent-Pilot / reports
124 Bytes
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  • 1 contributor
History: 1 commit
SOTAagi2030's picture
SOTAagi2030
Publish PocketIntent-Pilot offline intent classifier (selected run_sable)
d6ee3fa verified about 1 month ago
  • confusion_matrix.png
    42 Bytes
    Publish PocketIntent-Pilot offline intent classifier (selected run_sable) about 1 month ago
  • latency_by_device.csv
    82 Bytes
    Publish PocketIntent-Pilot offline intent classifier (selected run_sable) about 1 month ago