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
I am pleased to inform you that the dreambooth training has produced excellent results. It seems the previous difficulty arose from an incorrect learning rate. I have encountered a remaining challenge: all generated images tend to resemble the model, irrespective of the prompt utilized. Although the model was trained using the prompt "ohwx" and the class "woman," this issue persists even when the prompt is omitted or when a different subject, such as "man," is specified. Could you please offer some guidance on the potential cause of this occurrence? My objective is to generate images of other women/man in certain scenes who do not precisely replicate the trained model.
Have you had a chance to try hidream yet? I’ve been testing loras with the same data set as flux and it’s so much better. Not sure how it will cope with multiple subjects concepts but for my purpose it’s miles ahead.
Anyone else suddenly having issues fine tuning with kohya on Massed compute? I've done this like 50 times now the past 3 months and am suddenly getting errors
Thank you Dr. And grabbing the 1024px ones will be sufficient. No point going higher. And you already cropped to make the person occupy most of the photos yes? So I don't have to run your ultimate image process on them.
doing my first sdxl fine tune with using regimages. i had 54 training images, so it looks like it's using 55 reg images per epoch, does this look right? don't wanna waste 25h
Unlock the power of FLUX LoRA training, even if you're short on GPUs or looking to boost speed and scale! This comprehensive guide takes you from novice to expert, showing you how to use Kohya GUI for creating top-notch FLUX LoRAs in the cloud. We'll cover everything: maximizing quality, optimizing speed, and finding the best deals. With our exc...
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@Furkan Gözükara SECourses what is the result of training 15 pics of woman A then 10 pics of woman B, ohwx woman as token for every pic? Result would be like a mean of their looks?
I got the same result. If this is a specification of Flux, it is a big problem. I hope there is some way to avoid it by ingenuity during training. I will try to get the same result by using a caption file.
Dr. We are hopeful that you will be the first to teach us how to fine tune on Hi Dream Dev, I hear Dev actually is better than the full version. @Furkan Gözükara SECourses
Im new on LORA training and i have a question: what is if i want to train a full body (not only face and hairs and little bite of the upper body) LORA of a person. Can i train it on as example 1350 x 1080 or 1920 x 1080 or i need to train it on 1024 x 1024 too and crop the images? And can i generate other resolutions after training? Sorry for this dumb questions but i never trained a lora and in the tutorial all is trained and cropped by 1024 x 1024. Thanks alot
Ok, thank you. But the image sizes have no direct influence on the images I can generate later, right? Because the model only learns the object with the images, for example, and not the size. So if, for example, I have 50 images with a resolution of 1080 x 1350 that contain everything that is important for the LORA, I can also generate other resolutions later, such as 896 x 1152 (portrait), right? Because LORA training only learns the object?