Instructions to use mlx-community/silero-vad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/silero-vad with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir silero-vad mlx-community/silero-vad
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
Silero VAD MLX
This model was converted from onnx-community/silero-vad to MLX format.
Usage
from mlx_audio.vad import load
model = load("mlx-community/silero-vad")
timestamps = model.get_speech_timestamps("audio.wav", return_seconds=True)
print(timestamps)
For streaming, pass 512-sample chunks at 16 kHz or 256-sample chunks at 8 kHz:
state = model.initial_state(sample_rate=16000)
probability, state = model.feed(chunk, state, sample_rate=16000)
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Hardware compatibility
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