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
Yes. I love the feature of defining a mask as it allows. I've not tried regional prompter or whatever it's called, I looked at it and it seemed to be a step backwards in function
Total power over generations between latent couple and control net, tho to fully utilize latent couple, requires some skill with Photoshop or similar for precision. The control net segment preprocessor might have some potential too. I've not tried it just considered it.
Personally cosine and polynomial have given me good results. Seems to be a matter of just finding settings. There's a write up in discussions for dreambooth on GitHub that has a very thorough fleshing out of how to do your settings according to a formula. https://github.com/d8ahazard/sd_dreambooth_extension/discussions/547
NEW UPDATE Updated formulas for calculating frame resolutions. Also updates with permissions were carried out in the table with mathematics. The custom lr_scheduler has been moved to a separate doc...
@ashleyk I would not presume to know better than the good doctor.
I am mobile at this time and cannot access my dreambooth settings. The advantage I like of any scheduler on a curve is that it greatly helps with avoiding over fitting. Lots of ways to preserve the model you train on.
It's 6am here and bed time, but as I need to get back into training this weekend, ty for the link. I will definitely watch. I've been bookmarking several of your courses for references.
I plan to. His courses are fantastic. This weekend I have a lot of work I need to get done, so I'll be training to his spec and looking forward to the results
@Furkan Gözükara SECourses I'm trying to do dreambooth training using the Inkpunk model to get the same style but I'm having a few errors. Using 1 x A100 80GB 24 vCPU 125 GB RAM on Runpod.
I installed dreambooth manually, changed the requirements, but when training I get this error: AssertionError: from user code: File "/workspace/venv/lib/python3.10/site-packages/torch/random.py", line 23, in get_rng_state return default_generator.get_state() Set torch._dynamo.config.verbose=True for more information
depending on seed, cfg, etc... sometimes a model is better at 3.000 steps, other times at 20.000 steps, other times using filewords, other times not using it...
maybe i shoauldn't be using euler_a to compare? when comparing checkpoints at different steps... they produce very different stuff and it's hard to compare