Knowledge Distillation in PyTorch: Shrinking Neural Networks the Smart Way
Introduction What if your model could run twice as fast and use half the memory, without giving up much accuracy? This is the promise of knowledge distillation: training smaller, faster models to mimic larger, high-performing ones. In this post, we’ll walk through how to distill a powerful ResNet50 model into a lightweight ResNet18 and demonstrate a +5% boost in accuracy compared to training the smaller model from scratch, all while cutting inference latency by over 50%. ...