在 iPhone、iPad 和 Mac 上使用 Core ML 實現更快的 Stable Diffusion
Original: Faster Stable Diffusion with Core ML on iPhone, iPad, and Mac
In the era of rapidly advancing generative AI, deploying large deep learning models to users' personal devices (edge devices) has long been…
本文介紹如何利用 Core ML 技術在 Apple Silicon 晶片上加速 Stable Diffusion。透過模型量化（如 6-bit/8-bit）與 Apple 神經網路引擎（ANE）的優化，開發者能顯著降低記憶體佔用，在 iPhone、iPad 和 Mac 上實現本地端超快速的圖像生成，有效解決行動裝置記憶體不足（OOM）的痛點。
In the era of rapidly advancing generative AI, deploying large deep learning models to users' personal devices (edge devices) has long been a major challenge for developers. This technical blog post from Hugging Face details how to use Apple's Core ML framework to dramatically accelerate Stable Diffusion model inference on Apple Silicon devices — including iPhones, iPads, and Macs — while effectively addressing the out-of-memory (OOM) issues that commonly plague mobile devices.
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