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zencastr
/
laughter-detection

Audio Classification
Transformers
ONNX
Safetensors
multilingual
eat-laughter
audio-frame-classification
audio
sound-event-detection
laughter-detection
podcast
custom_code
Model card Files Files and versions
xet
Community

Instructions to use zencastr/laughter-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use zencastr/laughter-detection with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="zencastr/laughter-detection", trust_remote_code=True)
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModelForAudioFrameClassification
    model = AutoModelForAudioFrameClassification.from_pretrained("zencastr/laughter-detection", trust_remote_code=True, device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
laughter-detection / figures
828 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
alexcannan's picture
alexcannan
v0.1
849623f 14 days ago
  • inference_simple.svg
    94.3 kB
    v0.1 14 days ago
  • results-table.pdf
    186 kB
    xet
    v0.1 14 days ago
  • results-table.png
    342 kB
    xet
    v0.1 14 days ago
  • results-table.tex
    3.42 kB
    v0.1 14 days ago
  • training_simple.svg
    202 kB
    v0.1 14 days ago