使用 Diffusers 庫與 DreamBooth 技術微調 Stable Diffusion 完整指南
Original: Training Stable Diffusion with Dreambooth using Diffusers
This is a classic technical guide written by Hugging Face, detailing how to use their open-source diffusers library to fine-tune Stable…
本指南為 Hugging Face 官方發布的 DreamBooth 訓練教學。透過 diffusers 函式庫，開發者與創作者只需提供 3 到 5 張特定主體的照片，即可微調 Stable Diffusion 模型。文中詳細介紹了訓練原理、先驗保持損失（Prior Preservation Loss）的重要性，以及如何利用 8-bit Adam 和 xFormers 等技術在消費級 GPU 上完成訓練。
This is a classic technical guide written by Hugging Face, detailing how to use their open-source diffusers library to fine-tune Stable Diffusion models via DreamBooth. DreamBooth is a technique for implanting a specific subject — such as a particular person, pet, or object — into a text-to-image generation model. Users only need to prepare 3 to 5 photos of the subject and specify a unique identifier (e.g., "sks dog"), and the model learns the subject's characteristics. It can then place the subject in a wide variety of scenes, artistic styles, or actions while preserving its unique appearance.
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