Rectified flow is a generative modeling technique based on flow matching that interpolates between noise and data distributions. This library provides a PyTorch implementation including UNet-based models, reflow training procedures, and sampling utilities for generating images. It supports training with the accelerate library and includes implementations of followup research improvements.