@PyTorch
Arm has released a set of hands-on labs designed to help developers deploy PyTorch models using ExecuTorch across real edge devices. The labs walk-through: • Exporting models into lightweight .pte artifacts • Running optimized inference on Arm CPUs (XNNPACK + KleidiAI) • Offloading workloads to Ethos-U NPUs using TOSA and Vela • Visualizing model partitioning and performance behavior It’s a practical way to understand how models are executed across heterogeneous compute—and how to optimize for it. If you’re working on edge AI or exploring on-device inference, this is worth a look: https://t.co/cml4cBVF3Q #PyTorch #ExecuTorch #OpenSourceAI