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--- |
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title: Whisper Webui |
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emoji: ⚡ |
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colorFrom: pink |
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colorTo: purple |
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sdk: gradio |
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sdk_version: 3.3.1 |
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app_file: app.py |
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pinned: false |
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license: apache-2.0 |
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--- |
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
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# Running Locally |
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To run this program locally, first install Python 3.9+ and Git. Then install Pytorch 10.1+ and all the other dependencies: |
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``` |
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pip install -r requirements.txt |
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``` |
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Finally, run the full version (no audio length restrictions) of the app: |
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``` |
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python app-full.py |
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``` |
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You can also run the CLI interface, which is similar to Whisper's own CLI but also supports the following additional arguments: |
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``` |
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python cli.py \ |
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[--vad {none,silero-vad,silero-vad-skip-gaps,silero-vad-expand-into-gaps,periodic-vad}] \ |
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[--vad_merge_window VAD_MERGE_WINDOW] \ |
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[--vad_max_merge_size VAD_MAX_MERGE_SIZE] \ |
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[--vad_padding VAD_PADDING] \ |
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[--vad_prompt_window VAD_PROMPT_WINDOW] |
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[--vad_parallel_devices COMMA_DELIMITED_DEVICES] |
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``` |
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In addition, you may also use URL's in addition to file paths as input. |
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``` |
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python cli.py --model large --vad silero-vad --language Japanese "https://www.youtube.com/watch?v=4cICErqqRSM" |
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``` |
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## Parallel Execution |
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You can also run both the Web-UI or the CLI on multiple GPUs in parallel, using the `vad_parallel_devices` option. This takes a comma-delimited list of |
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device IDs (0, 1, etc.) that Whisper should be distributed to and run on concurrently: |
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``` |
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python cli.py --model large --vad silero-vad --language Japanese \ |
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--vad_parallel_devices 0,1 "https://www.youtube.com/watch?v=4cICErqqRSM" |
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``` |
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Note that this requires a VAD to function properly, otherwise only the first GPU will be used. Though you could use `period-vad` to avoid taking the hit |
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of running Silero-Vad, at a slight cost to accuracy. |
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This is achieved by creating N child processes (where N is the number of selected devices), where Whisper is run concurrently. In `app.py`, you can also |
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set the `vad_process_timeout` option. This configures the number of seconds until a process is killed due to inactivity, freeing RAM and video memory. |
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The default value is 30 minutes. |
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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 |
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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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Then either use the GitLab hosted container below, or check out this repository and build an image: |
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``` |
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sudo docker build -t whisper-webui:1 . |
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``` |
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You can then start the WebUI with GPU support like so: |
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``` |
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sudo docker run -d --gpus=all -p 7860:7860 whisper-webui:1 |
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``` |
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Leave out "--gpus=all" if you don't have access to a GPU with enough memory, and are fine with running it on the CPU only: |
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``` |
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sudo docker run -d -p 7860:7860 whisper-webui:1 |
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``` |
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# GitLab Docker Registry |
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This Docker container is also hosted on GitLab: |
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``` |
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sudo docker run -d --gpus=all -p 7860:7860 registry.gitlab.com/aadnk/whisper-webui:latest |
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``` |
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## Custom Arguments |
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You can also pass custom arguments to `app.py` in the Docker container, for instance to be able to use all the GPUs in parallel: |
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``` |
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sudo docker run -d --gpus all -p 7860:7860 \ |
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--mount type=bind,source=/home/administrator/.cache/whisper,target=/root/.cache/whisper \ |
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--restart=on-failure:15 registry.gitlab.com/aadnk/whisper-webui:latest \ |
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app.py --input_audio_max_duration -1 --server_name 0.0.0.0 --vad_parallel_devices 0,1 \ |
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--default_vad silero-vad --default_model_name large |
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``` |
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You can also call `cli.py` the same way: |
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``` |
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sudo docker run --gpus all \ |
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--mount type=bind,source=/home/administrator/.cache/whisper,target=/root/.cache/whisper \ |
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--mount type=bind,source=${PWD},target=/app/data \ |
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registry.gitlab.com/aadnk/whisper-webui:latest \ |
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cli.py --model large --vad_parallel_devices 0,1 --vad silero-vad \ |
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--output_dir /app/data /app/data/YOUR-FILE-HERE.mp4 |
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``` |
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## Caching |
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Note that the models themselves are currently not included in the Docker images, and will be downloaded on the demand. |
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To avoid this, bind the directory /root/.cache/whisper to some directory on the host (for instance /home/administrator/.cache/whisper), where you can (optionally) |
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prepopulate the directory with the different Whisper models. |
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``` |
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sudo docker run -d --gpus=all -p 7860:7860 \ |
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--mount type=bind,source=/home/administrator/.cache/whisper,target=/root/.cache/whisper \ |
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registry.gitlab.com/aadnk/whisper-webui:latest |
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``` |
