This project demonstrates the use of Olive to optimize an AI model for specific hardware, utilizing the Whisper Tiny English version as a case study. The optimized model is then deployed to the device and using ONNX Runtime we can execute both local and cloud-based inference.

Before beginning, ensure that you have the following:

1. Download Whisper-Tiny-Model from here

2. Follow the Olive tutorial for optimization here or Dowload converted model from here

3. Install Cuda 12.3 toolkit from Nvidia

4. Install Cudnn for cuda 12.3 from Nvidia

   Here a good example how to install Cuda and Cudnn. In that example is legacy version but approach is the same.

Clone the repository to your local machine with:

git clone https://github.com/onnxruntime/Whisper-HybridLoop-Onnx-Demo.git

or just download compiled version from Release.

For detailed instructions on how to optimize the Whisper model for specific hardware using the Olive engine and Follows, please see our detailed Tutorial on Model Optimization.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

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This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

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