The article presents the Decoupled Diffusion Transformer (DDT) architecture, demonstrating improved performance with a larger encoder in a diffusion model framework. It achieves state-of-the-art FID scores on ImageNet benchmarks and allows for accelerated inference by reusing encoders across steps. The implementation provides detailed configurations for training and inference, along with online demos.

CogView4-6B is a text-to-image generation model that supports a range of resolutions and offers optimized memory usage through CPU offloading. The model has demonstrated impressive performance benchmarks compared to other models like DALL-E 3 and SDXL, achieving high scores across various evaluation metrics. Users can install the necessary libraries and use a provided code snippet to generate images based on detailed prompts.