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 just trained a six-keyword Lora for SD 1.5 (poses). And it's nice to see that it produces results for all six keywords nicely, and just need a minimal Hires fix (0.3) for face. With AdamW8bit optimizer, with these settings (almost the same as I shared earlier, slightly modified and higher weights). Now I'm retraining with the same parameters, but I've turned on normalization, which also gave interesting results yesterday, but as I saw, it does match the Lora to the base model. I'll be curious to see what I end up with.
At the start of training, the model parameters are copied to the EMA parameters. At each gradient update step, the EMA parameters are updated using t...
@Dr. Furkan Gözükara do we have an up to date version of dreambooth and automatic1111 that is working yet or do i still need to train from older version?
DeepSpeed lives! Now correctly integrated, DeepSpeed allows for training SDXL's full U-net at 8 seconds per iteration on just ~12G of VRAM. See the documentation for more information! Features ...
a question on lora with various checkpoints: in the previous sd1.5 era, i could train a lora on sd1.5 or anylora checkpoint and use that lora on almost any checkpoints without fail. However, loras trained on & tested ok with sdxl model doesnt seem to work at all with other checkpoints (such as realVisXL) - it generates a lot of artifacts as if overtrained. Does anyone have idea why?
yes i too felt the same. Lora`s dont play well with models imo. Also i found , setting them to a 0.9 or less than that results in much controlled output.
i saw in your video that for auto cropping script that you have sent the dataset into the train tabl to resize it, do i need to do the same with my dataset after cropping it 512px x 768pxt?