Accelerating SD Turbo and SDXL Turbo Inference with ONNX Runtime and Olive
Introduction
SD Turbo and SDXL Turbo are two fast generative text-to-image models capable of generating viable images in as little as one step, a significant improvement over the 30+ steps often required with previous Stable Diffusion models. SD Turbo is a distilled version of Stable Diffusion 2.1, and SDXL Turbo is a distilled version of SDXL 1.0. We’ve previously shown how to accelerate Stable Diffusion inference with ONNX Runtime. Not only does ONNX Runtime provide performance benefits when used with SD Turbo and SDXL Turbo, but it also makes the models accessible in languages other than Python, like C# and Java.
Introduction
SD Turbo and SDXL Turbo are two fast generative text-to-image models capable of generating viable images in as little as one step, a significant improvement over the 30+ steps often required with previous Stable Diffusion models. SD Turbo is a distilled version of Stable Diffusion 2.1, and SDXL Turbo is a distilled version of SDXL 1.0. We’ve previously shown how to accelerate Stable Diffusion inference with ONNX Runtime. Not only does ONNX Runtime provide performance benefits when used with SD Turbo and SDXL Turbo, but it also makes the models accessible in languages other than Python, like C# and Java.