* It was trained using text conditions computed from T5. This aspect makes the pipeline better at following complex text prompts with intricate details.
* It is good at producing high-resolution images at different aspect ratios. To get the best results, the authors recommend some size brackets which can be found [here](https://github.com/PixArt-alpha/PixArt-sigma/blob/master/diffusion/data/datasets/utils.py).