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TransWithAI
/
Whisper-Vad-EncDec-ASMR-onnx

Audio Classification
Transformers
ONNX
Japanese
multilingual
voice-activity-detection
vad
whisper
speech-detection
asmr
japanese
whispered-speech
Model card Files Files and versions
xet
Community
3

Instructions to use TransWithAI/Whisper-Vad-EncDec-ASMR-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use TransWithAI/Whisper-Vad-EncDec-ASMR-onnx with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("audio-classification", model="TransWithAI/Whisper-Vad-EncDec-ASMR-onnx")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("TransWithAI/Whisper-Vad-EncDec-ASMR-onnx", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
Whisper-Vad-EncDec-ASMR-onnx
119 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
grider-transwithai's picture
grider-transwithai
Update README.md
6ac29e2 verified 6 months ago
  • .gitattributes
    1.52 kB
    initial commit 6 months ago
  • README.md
    8.69 kB
    Update README.md 6 months ago
  • inference.py
    25.9 kB
    Upload model and requirements files 6 months ago
  • model.onnx
    119 MB
    xet
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  • model_metadata.json
    370 Bytes
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  • requirements.txt
    233 Bytes
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