Step by Step Guide to Build an End-to-End Model Optimization Pipeline with NVIDIA Model Optimizer Using FastNAS Pruning and Fine-Tuning

The tutorial builds an end-to-end pipeline using NVIDIA Model Optimizer to train, prune, and fine-tune a model in Google Colab.

It prepares CIFAR-10 data loaders, defines a ResNet, and trains a baseline model with fixed seeds for reproducibility.

FastNAS pruning is applied to meet a target FLOPs budget, then the pruned subnet is restored and fine-tuned to recover accuracy.