This repository provides a PyTorch implementation of Classifier Free Guidance, a technique that enhances text-conditioned diffusion models by conditionally dropping text guidance during training to improve generation quality. It offers flexibility to combine multiple text embedding models such as T5 and CLIP, as demonstrated in research like eDiff-I. The library uses Python decorators to make text conditioning easy to integrate into any generative model.