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've written python scripts with chatGPT that will process the high resolution images for training by cutting them into 1024x1024 pieces with a bit of overlap.
0 runs, 0 stars, 0 downloads. This fine tuned checkpoint is based on Flux dev de-distilled thus requires a special comfyUI workflow and won't work very well ...
not really the higher the resolution the longer it takes to render obviously - and you get better results but also diminishing returns eventually - this was resized to 1080p i believe took 5min to render
i sent the workflow above - input video - play with the prompt and setting, make sure to match the skip steps with the normal scheduler step to equal 20 step of genning anything under that breaks teh genning
I already test some top Flux dev de-distilled model, quality quite dissapointed, most of them only good on realistic image, for the style only the same or even worse than Flux dev although time for render is double due to CFG >1. Are there any de-distilled models you guys can recommend and maybe can be used to train lora and finetuning ?
What would you guys recommend for a flux checkpoint training on Kohya for a character model.. i have 40 images on a 3090ti (24 gb, 64 gb of ram). More than batch size 1? Is current best practice not to caption our training sets and to use ohxw woman? Things change so fast in this world?
@Dr. Furkan Gözükara I'm currently using Flux Q8 on Kaggle , is there something better I can use for multi purpose? (realism,style etc). I saw in chat something about de distilled versions?
Anyone know the easiest way to finetune your own VLLM for image captioning? I've already got my own dataset, but there doesn't seem to be a straightforward way to actually carry out the finetuning process itself... I know there's already some good captioners out there, but I want to finetune my own