JoePenna/Dreambooth-Stable-Diffusion
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
Combines textual inversion and class-preservation techniques to fine-tune Stable Diffusion on limited GPU memory (24GB VRAM), supporting multi-concept training with optional captions and class regularization images to prevent semantic shift. Deployable across RunPod, Vast.AI, Google Colab, and local environments via Jupyter notebooks with built-in model pruning to compress trained weights from 11-12GB to ~2GB. Includes debugging guidance and recommends using celebrity token names rather than artist identities to mitigate training-data bias and respect creator attribution.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Jan 08, 2024
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