text2image-gui VS Dreambooth-SD-optimized

I read github

With the AMD guide

You can find NMKD here, and the readme should be quite simple to get it to work on your own machine for a basic SD setup: https://github.com/n00mkrad/text2image-gui

So assuming you are suing the "NMKD" GUI i found an existing issue on the github page: The Issue.

Source code is available here if you want to check that out, the download for the precompiled program is on itch.io.

The 1024x572 was from a comment talking about NMKD ,that mentions using OptimiseSD may run on less than 4GB.

Be sure to read the system requirements and the special AMD GPU info page.

Easiest way I have seen so far, working well for me. https://github.com/n00mkrad/text2image-gui/blob/main/DreamBooth.md

Hey guys im quite new to dream booth i tried the one in stabel diffusion but wasnt really satisfied with the output. Im lloking for a external dreambooth that could be started with anaconda but doesnt need 24 gb Vram i only have 12 Gb. I tried gammagec / Dreambooth-SD-optimizedbut he says you need at least 24 GB

Using this GitHub https://github.com/gammagec/Dreambooth-SD-optimized from this guide https://pastebin.com/xcFpp9Mr

I had pretty good results with 20 images of myself, 200 reg images and 6000 step using https://github.com/gammagec/Dreambooth-SD-optimized.

I use Automatic1111 for SD and then Dreambooth Optimized https://github.com/gammagec/Dreambooth-SD-optimized to do custom models.

Gammagec Dreambooth-SD-optimized - https://github.com/gammagec/Dreambooth-SD-optimized

I use this dreambooth repo to train the SD model. https://github.com/gammagec/Dreambooth-SD-optimized Here's the video that shows how to install it in very good detail. https://youtu.be/TwhqmkzdH3s He uses it to train in a face but you can use it to train in a style as well. I suggest taking about 15 or 20 detailed frames of the video and training it in as a style for the class name. You'll have to experiment with how many training steps to take. I suggest doing 1,000 steps at a time and testing out the model. Also don't leave the default "sks", the researchers forgot that that's a common acronym if you know what I mean. Do something like my_style1 so the model doesn't get confused with something else.

I'm using this guide: https://www.reddit.com/r/StableDiffusion/comments/xpoexy/yet_another_dreambooth_post_how_to_train_an_image/ to train locally with this repo https://github.com/gammagec/Dreambooth-SD-optimized on windows. Needs a 24gb card though.