/whisper-burn

A Rust implementation of OpenAI's Whisper model using the burn framework

Primary LanguageRustMIT LicenseMIT

Whisper Burn: Rust Implementation of OpenAI's Whisper Transcription Model

Whisper Burn is a Rust implementation of OpenAI's Whisper transcription model using the Rust deep learning framework, Burn.

License

This project is licensed under the terms of the MIT license.

Model Files

All the Whisper models that have been converted to work in burn are available in the whisper-burn space on Hugging Face. You can find them at https://huggingface.co/Gadersd/whisper-burn.

Installation & Usage

Before starting, ensure you have the necessary tools & libraries installed in your system. These instructions are for both CUDA and Mac users.

1. Clone the Repository

Clone the repository to your local machine using the following command:

git clone https://github.com/Gadersd/whisper-burn.git

Then, navigate to the project folder:

cd whisper-burn

2. Download Whisper Tiny English Model

Use the following commands to download the Whisper tiny English model:

wget https://huggingface.co/Gadersd/whisper-burn/resolve/main/tiny_en/tiny_en.cfg
wget https://huggingface.co/Gadersd/whisper-burn/resolve/main/tiny_en/tiny_en.mpk.gz

CUDA USERS

3. Set Environment Variable for Torch CUDA Version

Set your Torch CUDA version environment variable

export TORCH_CUDA_VERSION=cu113

4. Run the Application

Once you've finished setting up, you can run the application using this command:

cargo run --release audio.wav tiny_en

MAC USERS

3. Run the Application

Run the application with the following command:

cargo run --release audio.wav tiny_en

This usage assumes that "audio.wav" is the audio file you want to transcribe, and "tiny_en" is the model to use. Please adjust according to your specific needs.

Enjoy using Whisper Burn!