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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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# 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. Then |
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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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## 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 --mount type=bind,source=/home/administrator/.cache/whisper,target=/root/.cache/whisper whisper-webui:1 |
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``` |
