Arm-Examples/ML-examples

Arm Machine Learning tutorials and examples

What it solves

This repository provides a collection of practical machine learning examples and tutorials designed to help developers optimize and deploy AI models on Arm-based hardware, specifically targeting Neural Processing Units (NPUs) and Cortex-based platforms.

How it works

The project organizes a series of specialized examples that demonstrate different aspects of the ML pipeline on Arm hardware:

  • Hardware Acceleration: Examples for the Ethos-U NPU on Corstone-300 and Corstone-1000 platforms.
  • Library Integration: Demonstrations of how to use the KleidiAI library.
  • Model Optimization: Tutorials on pruning and clustering to reduce model weight size for Ethos NPUs.
  • Framework Integration: Guides on training Conformer networks for speech recognition using PyTorch/ExecuTorch and exporting them to Ethos-U.
  • TensorFlow Lite Deployment: A Jupyter notebook demonstrating RNN unrolling for .tflite format export.

Who it’s for

Embedded systems developers and ML engineers who are targeting Arm Cortex and Ethos NPU hardware for edge AI deployment.

Highlights

  • Support for Arm Ethos-U NPUs and Corstone reference platforms.
  • Examples for model compression techniques like pruning and clustering.
  • Integration with PyTorch, ExecuTorch, and TensorFlow Lite.
  • Specific implementations for speech recognition using the Conformer network.