The MNIST and ImageNet examples below provide illustrative usages of (plain or nested) FSDP, saving and consolidation of model checkpoints, as well as gradient checkpointing.
Starting examples of FSDP in PyTorch/XLA
Training MNIST and ImageNet with FSDP
MNIST and ImageNet classification can often be used as starting points to build more complicated deep learning models. We provide the following FSDP examples on these two datasets:

MNIST: test/test_train_mp_mnist_fsdp_with_ckpt.py (it also illustrates checkpoint saving and consolidation)
ImageNet: test/test_train_mp_imagenet_fsdp.py
