Using DreamBooth on SD on a 3090 w/24gb VRAM (about 1.5 hrs to train)

This page summarizes the projects mentioned and recommended in the original post on reddit.com/r/StableDiffusion

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  • 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. (by JoePenna)

    Here is a version on put on RunPod which seems to work for me so far- https://github.com/JoePenna/Dreambooth-Stable-Diffusion/

  • Stable-textual-inversion_win

    Would it be possible for you to add this new code in the "regular" textual inversion code? like in this one : https://github.com/nicolai256/Stable-textual-inversion_win - I'm using a 3090, batch size of 3, workers 10, size 384 - works pretty good but if your modification could reduce the VRAM, it could go faster.

  • Zigi

    Delete the most useless function ever: context switching.. Zigi monitors Jira and GitHub updates, pings you when PRs need approval and lets you take fast actions - all directly from Slack! Plus it reduces cycle time by up to 75%.

  • bitsandbytes

    8-bit CUDA functions for PyTorch

    https://github.com/TimDettmers/bitsandbytes https://huggingface.co/blog/hf-bitsandbytes-integration

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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