XavierXiao/Dreambooth-Stable-Diffusion

Health v2 · maintenance only

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7738 stars · 795 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

An implementation of Google's Dreambooth fine-tuning method applied to Stable Diffusion, enabling personalization of a text-to-image diffusion model with a few example images. It is built on top of the Textual Inversion codebase but fine-tunes the entire diffusion model rather than just word embeddings.

Use cases

• fine-tune stable diffusion on photos of my dog
• personalize a text-to-image model with a few images
• train dreambooth on stable diffusion v1.4
• generate images of a specific subject after fine-tuning
• reduce GPU memory when fine-tuning the UNet with gradient checkpointing

When to choose

• you want the original minimal Dreambooth implementation for Stable Diffusion v1
• you want to fine-tune the full UNet rather than only embeddings
• you need a research-grade reference implementation based on the Textual Inversion codebase

When to avoid

• you need actively maintained support for newer Stable Diffusion versions like SDXL
• you want a polished tool with a UI or one-click training
• you need memory-efficient training on consumer GPUs beyond what this codebase offers

Facets

library · maturity maintenance

llm-training machine-learning image-processing deep-learning image-processing artificial-intelligence python dreambooth stable-diffusion fine-tuning text-to-image diffusion-models pytorch-lightning gpu

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