使用 ONNX Runtime 與 Olive 加速 SD Turbo 和 SDXL Turbo 推論
Original: Accelerating SD Turbo and SDXL Turbo Inference with ONNX Runtime and Olive
SD Turbo and SDXL Turbo are single-step/few-step text-to-image models from Stability AI, with their core innovation being Adversarial…
Hugging Face 介紹了如何結合微軟的 ONNX Runtime (ORT) 與 Olive 優化工具，來加速 SD Turbo 和 SDXL Turbo 模型。透過 Olive 的硬體感知優化流程，開發者可以輕鬆將 PyTorch 模型轉換為 ONNX 格式，並進行 FP16 量化與算子融合。這套方案特別適合在 Windows (透過 DirectML) 或 NVIDIA GPU (透過 CUDA) 上部署，能顯著降低單步圖像生成的延遲，非常適合需要即時互動的應用場景。
SD Turbo and SDXL Turbo are single-step/few-step text-to-image models from Stability AI, with their core innovation being Adversarial Diffusion Distillation (ADD) technology that enables extremely fast real-time generation. However, to achieve peak performance in production environments or on edge devices (such as Windows PCs), optimization at the level of the underlying inference engine is also required.
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