US EditionEC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing – Hoffeldt
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EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing – Hoffeldt
Apple Machine Learning Research Diffusion transformers have been widely adopted for text-to-image synthesis. While scaling these models up to billions of parameters shows promise, the effectiveness of scaling beyond current sizes remains underexplored and challenging. By explicitly exploiting the computational heterogeneity of image generations, we develop a new family of Mixture-of-Experts (MoE) models (EC-DIT) for diffusion transformers with …
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