Art-alpha. Some notes about this pipeline: It uses a Transformer backbone (instead of a UNet) for denoising. As such it has a similar architecture as DiT. 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 w