FFCV is a drop-in data loading library that dramatically increases throughput during model training by optimizing how training data is fed to ML models. It works with existing PyTorch training pipelines, requiring only replacing the data loader. The library is designed for computer vision workloads but supports other ML workloads, and ships with prepackaged benchmarks for ImageNet and CIFAR-10.