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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
1.09 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
alexcannan's picture
alexcannan
v0.1
849623f 9 days ago
  • eval
    v0.1 9 days ago
  • figures
    v0.1 9 days ago
  • .gitattributes
    1.71 kB
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  • LICENSE
    1.07 kB
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  • LICENSE-EAT
    1.07 kB
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  • README.md
    7.53 kB
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  • config.json
    9.96 kB
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  • configuration_laughter.py
    1.98 kB
    v0.1 9 days ago
  • events.py
    3.52 kB
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  • events_onnx.py
    6.99 kB
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  • export.json
    2.66 kB
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  • laughter_core.py
    4.06 kB
    v0.1 9 days ago
  • model.onnx
    362 MB
    xet
    v0.1 9 days ago
  • model.safetensors
    360 MB
    xet
    v0.1 9 days ago
  • model_fp16.onnx
    182 MB
    xet
    v0.1 9 days ago
  • model_fp16_opset23.onnx
    183 MB
    xet
    v0.1 9 days ago
  • modeling_laughter.py
    12.3 kB
    v0.1 9 days ago
  • pipeline_laughter.py
    7.65 kB
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  • preprocessor_config.json
    251 Bytes
    v0.1 9 days ago
  • release-manifest.json
    8.41 kB
    v0.1 9 days ago