Hello everyone. I am Dr. Furkan Gözükara. PhD Computer Engineer. SECourses is a dedicated YouTube channel for the following topics : Tech, AI, News, Science, Robotics, Singularity, ComfyUI, SwarmUI, ML, Artificial Intelligence, Humanoid Robots, Wan 2.2, FLUX, Krea, Qwen Image, VLMs, Stable Diffusion
oh ok yeah that makes sense now. I just figured probably one of your training images didn't have the glasses described in the caption, but then again the frames of the glasses aren't super bold and noticeable from a distance so that could be another reason
does anyone know if normal alternating via prompt such as [x|y] where it alternates between x and y each step is still usable in a natural language style model like flux?
now just seen, from all the png kpeg attachments that there is one zip file, .. I downloaded. I have the latest branch kohya. now i will start the training.
Do not skip any part of this tutorial to master how to use Stable Diffusion 3 (SD3) with the most advanced generative AI open source APP SwarmUI. Automatic1111 SD Web UI or Fooocus are not supporting the #SD3 yet. Therefore, I am starting to make tutorials for SwarmUI as well. #StableSwarmUI is officially developed by the StabilityAI and your m...
one test that you can do is training without the class just "ohwx" leve the token man untouched, then trigger ohwx and see if is doing something or is ignored completely, if that its the case thats the reason why concepts bleed and is not learning anything from the captions
I trained 2 person lora (nmwx for myself and ohwx for my wife), all images of me tagged with nmwx, despite prompting simply "nmwx" it returned images of my wife. BUT its very consistent that all "man" return me and all "woman" prompts returns my wife. So it looks like the model just overfitted for all men to look like me and all women look like my wife.
Also "nmwx man, HUGO BOSS advertisement" and "man, HUGO BOSS advertisement" return 99.5% the same image and likeness, just minor details changed.
BTW the 2 character lora works amazing. no bleeding between the two characters for me and can generate both within one image. Probably because its two genders, i'm doubting it would work if its two men though without training the encoder