MobileDiffusion: Rapid text-to-image generation on-device

MobileDiffusion: Rapid text-to-image generation on-device January 31, 2024Posted by Yang Zhao, Senior Software Engineer, and Tingbo Hou, Senior Staff Software Engineer, Core ML Quick links Share Copy link × Text-to-image diffusion models have shown exceptional capabilities in generating high-quality images from text prompts. However, leading models feature billions of parameters and are consequently expensive to run, requiring powerful desktops or servers (e.g., Stable Diffusion, DALL·E, and Imagen). While recent advancements in inference solutions on Android via MediaPipe and iOS via Core ML have been made in the past year, rapid (sub-second) text-to-image generation on mobile devices has remained out of reach. To that end, in “MobileDiffusion: Subsecond Text-to-Image Generation on Mobile Devices”, we introduce a novel approach with the potential for rapid text-to-image generation on-device. MobileDiffusion is an efficient latent diffusion model specifically designed for mobile devices. We also adopt DiffusionGAN to achieve one-step sampling during inference, which fine-tunes a pre-trained diffusion model while leveraging a GAN to model the denoising step. We have tested MobileDiffusion on iOS and Android premium devices, and it can run in half a second to generate a 512x512 high-quality image. Its comparably small model size of just 520M parameters makes it uniquely suited for mobile deployment.        Rapid text-to-image generation on-device. Background The relative ine...