Dreambooth in 11GB of VRAM

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

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  • efficient-dreambooth

    [Moved to: https://github.com/smy20011/dreambooth-docker]

  • diffusers

    🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch (by ShivamShrirao)

    In anaconda with Admin Permission I did: git clone https://github.com/ShivamShrirao/diffusers then ran conda install -c conda-forge diffusers (said yes)

  • SonarQube

    Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.

  • stable-dreambooth-optimized

    Dreambooth implementation based on Stable Diffusion with minimal code.

  • This is my repository with the updated source and a sample launcher: https://github.com/matteoserva/memory_efficient_dreambooth

  • fast-stable-diffusion

    fast-stable-diffusion, +25-50% speed increase + memory efficient + DreamBooth

    implemented here https://github.com/TheLastBen/fast-stable-diffusion , 800 steps in less than 13 minutes, 2000 steps in 30 minutes

  • Dreambooth-Stable-Diffusion-cpu

    Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion

    This https://github.com/andreae293/Dreambooth-Stable-Diffusion-cpu I believe should produce as ckpt file. You're probably testing the CPU on the hugging face version.

  • 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)

  • InfluxDB

    Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Data Platform where developers build real-time applications for analytics, IoT and cloud-native services in less time with less code.

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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