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
When I try to use txt2image the first image is generated normally but when I try to generate the next one it shows "RuntimeError: CUDA out of memory. Tried to allocate 58.00 MiB (GPU 0; 4.00 G...
Is there an existing issue for this? I have searched the existing issues and checked the recent builds/commits What happened? In a dual-GPU Windows 10 system (2 x RTX-3090), only the first GPU is b...
I just trained with a very interesting set of images. Even though I selected the best photos, I could only find the best d_coef value for a quarter of them. I tried 0.85, it didn't come out strong. With 1.02 it was too strong, and even with 0.95. Finally, with 0.9 I managed to get a near perfect Lora. On another set of images, I managed to get one that turned out perfect the first time, even though there was nothing special about the photos. So there are still some exceptions where, even if the graph is good, you still need to polish the final result a bit.
@Dr. Furkan Gözükara i am on the 2nd episode of your course on udemy, have you in latter courses also specified how to prompt stable diffusion to generate amazing images like how people do (chubby:0.4) something like that
Hi, @Dr. Furkan Gözükara some questions about Kohya training for SD. I would like to train clothing based on a culture. Basically, using any checkpoint, I can just invoke them to wear the clothing with just a keyword. Would a Lora be the best option? Also, when training, how do you best caption the dataset so that the Lora does not remember the background, the face, color of the clothing, physical weight of the person, etc. I only want the clothing, and want to be able to determine the colors. How many images would be minimum for clothing? And what's the best way to caption? I have tried so many different ways, and haven't been very successful.