Part 4: Edge Deployment of an 86M Parameter Audio Transformer

Post 3 ended with three numbers: 97.4% test accuracy, 100% precision, 0 false positives. All of it measured on a MacBook. That was enough to prove the model could learn first crack. It did not prove the model could run where I needed it: next to a coffee roaster, on a Raspberry Pi 5, listening through a USB microphone during a live roast. The first Pi run was "it kind of works". Export the PyTorch checkpoint to ONNX FP32, copy the 345MB file across, run inference. The result was 9.4 seconds per