The training method applies adversarial supervision to the text stream of a multimodal diffusion transformer. For two-step sampling, the authors provide a separate de-distillation LoRA and a workflow that pairs it with the main checkpoint.
The small step count makes the release useful for fast visual iteration and experimentation with distilled image models. Users can start in the hosted demo and use the downloadable workflow to adjust sampling and compare outputs locally.
