A PyTorch library implementing Schedule-Free optimization algorithms that eliminate the need for learning rate schedules and warmup phases during training. It provides drop-in replacements for standard optimizers like SGD and AdamW, replacing momentum with interpolation and averaging. The approach is derived from the paper ‘The Road Less Scheduled’ (arXiv:2405.15682).