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Update README

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@@ -59,8 +59,21 @@ The default value is 30 minutes.
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  python app.py --input_audio_max_duration -1 --vad_parallel_devices 0,1 --vad_process_timeout 3600
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  ```
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  You may also use `vad_process_timeout` with a single device (`--vad_parallel_devices 0`), if you prefer to always free video memory after a period of time.
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  # Docker
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  To run it in Docker, first install Docker and optionally the NVIDIA Container Toolkit in order to use the GPU.
 
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  python app.py --input_audio_max_duration -1 --vad_parallel_devices 0,1 --vad_process_timeout 3600
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  ```
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+ To execute the Silero VAD itself in parallel, use the `vad_cpu_cores` option:
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+ ```
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+ python app.py --input_audio_max_duration -1 --vad_parallel_devices 0,1 --vad_process_timeout 3600 --vad_cpu_cores 4
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+ ```
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+
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  You may also use `vad_process_timeout` with a single device (`--vad_parallel_devices 0`), if you prefer to always free video memory after a period of time.
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+ ### Auto Parallel
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+
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+ You can also set `auto_parallel` to `True`. This will set `vad_parallel_devices` to use all the GPU devices on the system, and `vad_cpu_cores` to be equal to the number of
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+ cores (up to 8):
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+ ```
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+ python app.py --input_audio_max_duration -1 --auto_parallel True
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+ ```
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+
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  # Docker
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  To run it in Docker, first install Docker and optionally the NVIDIA Container Toolkit in order to use the GPU.