AMD Ryzen™ AI Software includes the tools and runtime libraries for optimizing and deploying AI inference on your AMD Ryzen™ AI based PC. It enables developers to quickly build and run a variety of AI applications for Ryzen™ AI. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Ryzen™ AI.
This repository contains the demos, examples and tutorials, demonstrating usage and capabilities of the Ryzen™ AI Software. It is a subset of the Ryzen™ AI Software release.
Follow the instructions at Ryzen™ AI Software for installation.
Due to the presence of large files in some examples/tutorials, Git Large File Storage (LFS) has been configured in this repository. Follow the instructions below to ensure Git LFS is properly set up:
- Install Git LFS by downloading it from the official website
- After installation, run the following command in your terminal to set up Git LFS on your machine:
git lfs install
- Clone the repository (or a fork of it):
git clone https://github.com/amd/RyzenAI-SW.git
- Pull the actual LFS files:
git lfs pull
To run the demos and examples in this repository, please follow the instructions of README.md in each directory.
- A Getting Started Tutorial with a fine-tuned ResNet model
- Hello World Jupyter Notebook Tutorial
- Getting Started ResNet50 Tutorial on iGPU
- Run Vitis AI ONNX Quantizer example
- Real-time object detection with Yolov8
- Run multiple concurrent AI applications with ONNXRuntime
- Run Ryzen AI Library example
- Run ONNX end-to-end examples with custom pre/post-processing nodes running on IPU
- RAG LLM Sample
