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'm using RX6600 and my parameteres are: --medvram --precision full --no-half --opt-sub-quad-attention --sub-quad-q-chunk-size 512 --sub-quad-kv-chunk-size 512 --sub-quad-chunk-threshold 80 Is ...
What are your opinions on identical training parameters but different GPUs and how that relates to quality? i.e. It seems to me that when I train on a 4090, the results are superior than if I train on a A5000 - this is with identical training parameters. I would expect some speed differences, but not quality. Am I crazy? Has anybody else noticed similar things?
After a couple of weeks I find that d_coef 0.75 is enough for SD 1.5 Lora prodigy training, but if it is strong, 0.6 helps. You don't need to make it stronger to train persons. This is true for 5 reps for 20 pictures, 4 reps for 25 pictures (20x5=25x4=100).
Hello everyone, I have a quick question. I'm currently training a stable diffusion model using Kaggle, and I'm wondering about the required resolution for the training images. Do they need to be 1024x1024 pixels? I'm asking because my images are currently 512x512 pixels. I'm looking for clarification on this point,
Master Stable Diffusion XL Training on Kaggle for Free! Welcome to this comprehensive tutorial where I'll be guiding you through the exciting world of setting up and training Stable Diffusion XL (SDXL) with Kohya on a free Kaggle account. This video is your one-stop resource for learning everything from initiating a Kaggle session with dual ...