使用 JAX 與 Cloud TPU v5e 加速 Stable Diffusion XL 推理
Original: 🧨 Accelerating Stable Diffusion XL Inference with JAX on Cloud TPU v5e
With the widespread adoption of high-quality open-source image generation models like Stable Diffusion XL (SDXL), reducing inference…
Hugging Face 發表技術指南，展示如何結合 JAX 框架與 Google 最新 Cloud TPU v5e 晶片來加速 SDXL 推理。透過 JAX 的即時編譯（JIT）與 Diffusers 庫的 Flax 支援，開發者能以極高性價比進行大規模圖像生成。文中提供實作步驟與效能基準測試，為尋求 GPU 替代方案的團隊提供高效能選擇。
With the widespread adoption of high-quality open-source image generation models like Stable Diffusion XL (SDXL), reducing inference latency and controlling compute costs in production environments has become a key challenge for many development teams. Hugging Face's official blog published a technical guide detailing how to leverage the JAX framework and Google Cloud TPU v5e hardware to dramatically accelerate SDXL inference.
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