that sounds weird ratio but you can train with it
that sounds weird ratio but you can train with it
Fno issues
Ffor more details i recommend after training do 2x upscale
FYouTubeSECourses
If you want to generate the very best AI videos and images on your Windows computer locally this is the tutorial that you were looking for. Literally 1-click to install most powerful and advanced generative AI interface SwarmUI (with Flash Attention, Sage Attention, Triton, DeepSpeed, xFormers, RTX 5000 series perfect compatibility) and download...
Swhat ratio you recommend for full or half body training or is it best to crop them manually to 1024 x 1024 with the most of body and face what is possible
Sif it gets best quality with 1024px i cropped it no problem 
Fi trained 1024x1024 it works perfect
Fas long as your dataset good it will work
Sok last question: would you recommend captions. I think I read in one of your posts that it doesn't help with LORAs, is that still the case?
Sspecific on person loras
Fjust ohwx man or ohwx woman
SOK thank you so much i appreciate your work and this much Research 
Fty too
SHey guys, can we use a fine-tune flux checkpoint for impainting ? Or not recommended ?
Fyou can use
N@Furkan Gözükara SECourses is there a tutorial or explaination on how to determine if the model is overfit or not? I know it was mentioned somewhere, but I cant find a specific clear instructions. Thank you!
Fonly way is generating samples
Fsadly loss rate is meaningless
T@Furkan Gözükara SECourses Will you make a video to tell us how to train HiDream by using Dreambooth in MassedCompute Cloud?
Fyes i plan to. the things that comes never ending :d
TThanks very much, I'd like to use HiDream but without Dreambooth, not much use for me for now.
I know you are gonna make it ! Thanks @Furkan Gözükara SECourses
I know you are gonna make it ! Thanks @Furkan Gözükara SECourses
SDo you think it worth it compared to flux dev finetune ?
TFlux has too many internal censorships
�Has anyone fine tuned on pixelwave checkpoint?
�Or made lora
Fi did
FMedium
Thoroughly experimented with Fine-Tuning / DreamBooth training of Flux-dev-de-distill, PixelWave v03, Verus Vision and base FLUX Dev model…
Fwhat i care is multi concept
Fif works or not
Fotherwise for single concept flux pretty much amazingly working
EHello, I want to train sdxl koyha_ss on massed compute with A100 graphic card, I use the Tier1_48_GB_Faster_v2 config but I don't know what epoch I should set. I only have 8 images and I use all 5000 reg images. From what I understand, I should aim for 3000-5000 total steps. So I'm currently trying with the default settings of the configuration but setting 400 repeats so I have about 3200 steps...
- Is 400 repeats with 1 epoch and 8 pictures good?
- I set a batch size of 4 since the A100 gpu has 80gb of memory. Is this right?
- Could I optimize the config better to be faster or more efficient for A100 gpu?
EAlso, on massed compute, I see
Ah and if it's only 8 portrait images, do I want captions? From what I understand no
Thanks
Could not find TensorRTAh and if it's only 8 portrait images, do I want captions? From what I understand no
Thanks
Fnot important
F8 images really low
Fso go up to 300 epochs
Fsince it is sdxl
Fmake sure to use reg images
Ffor kohya
Fyou need to test repeating to be able to use class images
F400 repeat 1 epoch sounding good
Fmake sure to save once every n steps
EOk, and is the tier1 48gb config optimal for A100 graphic card with 80gb or I should change something to make it better and use more available memory? Batch size around 4-7? Do you recommend onetrainer finetune over kohya_ss dreambooth?
Thank you for the quick answer
Thank you for the quick answer
Fi dont recommend change anything it is best quality 
EOk
I'll try to give results here if I find the best sweet spot for my number of training images!
I do think it could be useful to have somer kind of pinned message with recommended setups of epoch #, repeat # and such specific to the # of images, or at least a ballpark close to it
Like 8 images: 400 repeats, 1 epoch
I'll try to give results here if I find the best sweet spot for my number of training images!
I do think it could be useful to have somer kind of pinned message with recommended setups of epoch #, repeat # and such specific to the # of images, or at least a ballpark close to it
Like 8 images: 400 repeats, 1 epoch
Fsadly there isnt much but i usually recommend 200 epoch
Fhowever your train image count too low
Fmore is better
EYeah I only have 8 images, I'm hoping I can finetune a model and generate decent enough images to be able to train with more images... Not sure how that will go lol