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
are you using the runpod kohya template by any chance? i had never noticed until watching the good dr's video that if you don't kill auto1111, 25-30% of the vram is getting sucked up before you start
i typically just reduce the batch size until it works, or throw on xformers, but i'm going to retry a few of them without cheating since apparently its bad juju
Oh, i see, yeah, let me do it as well. potential, means, when i run training, it doesnt take load on gpu it should take....usually, when the temperature gets higher, when the gpu is totally using it's power, but when i run training, with kohya, it only gets half of the temperature, compared to it usually takes.
Fixed to work tools/convert_diffusers20_original_sd.py. Thanks to Disty0! PR #1016 The issues in multi-GPU training are fixed. Thanks to Isotr0py! PR #989 and #1000
The only thing that broke, it seems, was Blip captioning, but as I recall, I was using some type of rollback version of something. I think it was transformers. Honestly most of these captions tools are lousy and if you are using a smaller data-set manual captioning is best
Can I do multi-gpu training in Koyha if the graphics cards are different models/different Vram? (example, RTX 3080 and RTX 3090). Sorry to ask before testing, it's that I need a new power supply if I want to use both cards.
Does anyone know the Syntax for the regional prompter well. I'm getting better with prompts but if I have two Character Loras what's the best way to set up the prompt?
I'm getting [virtualMemoryBuffer.cpp::nvinfer1::StdVirtualMemoryBufferImpl::resizePhysical::140] Error Code 2: OutofMemory when attempting to generate the TensorRT Default Engine
I have 12.3 installed, but it is not set in Path except that CUDA_PATH_V12_3 is set to that version. I installed 12.3 because it was the only way to check the samples with Visual Studio 2022.
Updating torch, torchvision, and xformers tossed another error saying torch could not access the GPU. It said I can set a flag, so it won't run the check, but I don't want to do that.