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
Batch rename files and folders in a snap. Perfect for any kind of file renaming including music and photo files. Preview your files before renaming and undo erroneous renaming jobs.
Batch rename files and folders in a snap. Perfect for any kind of file renaming including music and photo files. Preview your files before renaming and undo erroneous renaming jobs.
@Dr. Furkan Gözükara You've released a lot of new stuff! Now I just have to find the time to study it all) I don't understand how classes work, I've been trying to figure it out for how long, I can't get it. Physically, when we train a large model on characters, we roughly divide into a man and a woman. And if on subjects? Then every class is a subject? Car, Chair, Door, bag or sheep, Dragon, whale
And then I haven't seen anyone use the indicators, and here is the Reg_1 folder, how the learning structure should look in it. How to write files in it and what should they be?
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 ...
Im trying to find captioning techniques in your guides but couldnt get a clear idea. The SOTA you mentioned captions the image. Is that the one we need to use for Dreambooth/ Lora? Is Ohwx still best way to go to name someone? I saw some YT videos saying name to celebrity with high similarity is better way.
if you train for face , the lora is pretty overwhelming at times and very underwhelming at times.. Here is what i found :
Test with lora weights , this will again change with each models , so running a xyz plot will help find a balanced weight
Adetailer! - again run a xyz plot for denoising strength. Last time when i created a lora , the strength i was comfortable with was 0.4 , now its 0.1-0.15 , very low. Even at 0.3 , its bringing very bad facial features , and beyong 8 , itsjust pasting face on the face like bad photoshop.
Balance with CFG value as well. This will give overall creativity vs very close to prompt creation
EAch model will give different results , so use same seed and try different models to see which is good. Also use different version of models to see which is good. Eg: collosus XL model gave me bad result in its latest version. so dont update to latest models , its not what we think , its not some software..
7.Few things i felt which can change the outcome of face : Lora weight , Ohwx woman/man weight (use brackets to increase its weight or number) , Adetailer denoising strength , certain sampler , face restoration feature - i kept codeformers to 0.3 , face retoration back in adetailer. Will update if anything to be added
These are interesting things. In the last few Lora's I've coached women, I never adjusted the Lora's weight, it was always 1 and never modify CFG (always on 7). I had to use the Hires Fix to make the face even better, but many times it brought the person up nicely without it. But I'm tired of repeating the parameters, if you're interested, check out my comments here.
this might sound very weird , but i feel automatic1111 starts to give better results after some image creation.. like it warms up after some images.. this is totally absurd thought.. just my feeling..
Also if you are getting abnormal images , switch to 1024x1024 , it will start to give better results as its the base res. Also restarting auto1111 is also a not bad idea.
Hello I ran into this issue during the kaggle install, --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[2], line 8 5 import threading 7 from flask import Flask ----> 8 from pyngrok import ngrok, conf 10 conf.get_default().auth_token = "---" 12 os.environ["FLASK_ENV"] = "development"
My settings for Hires Fix: 15 steps with 0.4 noise and 4x_NMKD-Superscale-SP_178000_G, but the images above were taken without a hires fix or adetailer, I simply generated them.
I have already trained in clothes and style. Prodigy has worked really well for me and I now know what to look out for on Tensorboard to get a good result. I'd like to make a fairly complex conceptual Lora. It's been on hold for a few weeks, but based on the experience of the last training sessions I might start again, but there's no urgency. It will also be a NSFW Lora, partly done by others, but not on a photo basis, but with animation. We'll see how it goes. It works as a separate Lora now, the challenge here will be the balance of kneading 4-5 concepts into one.