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Nikeytas
/
videomae-crime-detector-improved

Video Classification
Transformers
Safetensors
videomae
Model card Files Files and versions
xet
Community

Instructions to use Nikeytas/videomae-crime-detector-improved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Nikeytas/videomae-crime-detector-improved with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("video-classification", model="Nikeytas/videomae-crime-detector-improved")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForVideoClassification
    
    processor = AutoImageProcessor.from_pretrained("Nikeytas/videomae-crime-detector-improved")
    model = AutoModelForVideoClassification.from_pretrained("Nikeytas/videomae-crime-detector-improved", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
videomae-crime-detector-improved
345 MB
Ctrl+K
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  • 1 contributor
History: 4 commits
Nikeytas's picture
Nikeytas
Event-based VideoMAE model - Accuracy: 0.750 (Violent vs Non-Violent)
034927b verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.17 kB
    Event-based VideoMAE model - Accuracy: 0.800 (Violent vs Non-Violent) about 1 year ago
  • config.json
    777 Bytes
    Event-based VideoMAE model - Accuracy: 0.800 (Violent vs Non-Violent) about 1 year ago
  • model.safetensors
    345 MB
    xet
    Event-based VideoMAE model - Accuracy: 0.750 (Violent vs Non-Violent) about 1 year ago
  • preprocessor_config.json
    415 Bytes
    Upload processor about 1 year ago