A simple GUI made with gradio
to use Whisper.
conda
added to PATH.git
installed and added to PATH. See instructions.ffmpeg
installed and added to PATH. See instructions for Windows, Linux or macOS.Optionally, to use Nvidia GPU on Windows:
Note: For AMD GPUs (ROCm), GPU support for Whisper is only available in Linux.
whisper-gui.bat
file. In Linux / macOS run the whisper-gui.sh
file. Follow the instructions and let the script install the necessary dependencies. After the process, it will run the GUI in a new browser tab.Otherwise, manual steps are:
conda create --name whisperx python=3.10
conda activate whisperx
conda install pytorch::pytorch==2.0.0 torchaudio==2.0.0 -c pytorch
conda install pytorch==2.0.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia
pip install torch==2.0.0 torchaudio==2.0.0 --index-url https://download.pytorch.org/whl/rocm6.0
conda install pytorch==2.0.0 torchaudio==2.0.0 cpuonly -c pytorch
pip install git+https://github.com/m-bain/whisperx.git
pip install gradio
git clone https://github.com/Pikurrot/whisper-gui
To run the program every time, you can just run the same whisper-gui.bat
or whisper-gui.sh
(whatever your OS), which will also automatically check for updates of this repository.
Your transcriptions will be saved by default in the outputs
folder of the repository.
Otherwise, to run manually:
conda activate whisperx
python main.py --autolaunch
To run this software in a docker container, visit this dockerhub project.
Thank you 3x3cut0r!
This project is primarily distributed under the terms of the MIT License. See the LICENSE file for details.
Third-Party Code
Portions of this project incorporate code from WhisperX, which is licensed under BSD-4-Clause license. This code is used in accordance with its license, and the full text of the license can be found within the relevant source files.