Trained on a dataset which i planned to use for SDXL, but i never got satisfying results . Just a small test with a few images ( basic capitations for now ) and only 800 steps. Will change that later to natural language.

Most used words should be atmospheric, moody, calm, soothing, serene, mysterious ... and assorted ( the images without capitation ... well, that is a capitation, forgot that Kohya picks the name of the folder if no .txt file is present :D )

• Order: First 2 Images with LoRA / without LoRA, after that, reversed order

• Has more/less impact in specific cases ( for now )

Did quite some testing with Flux LoRA's iv'e made and got really crazy results. Even after only like 100 - 200 steps it got the concept and lower/higher strength from base 1 has always a huge impact, but something is always left and it feels like you can kinda pick specific parts from the images it was trained on without it using the whole image ( like you only want the the yellow clothing but nothing else )

Made like 30 LoRA's so far ( only for testing purposes ) and what you can do with just a few images is baffling.

Might be just a fluke, who knows.