Any recommendations on how to setup A1111 on AWS?
Any recommendations on how to setup A1111 on AWS?
SOr Forge
Fyou dont need caption if your dataset is consisten enough
Fenable shared vram
Finitial loading uses VRAM
Fi trained on my rtx 3060 yesterday perfectly training
Fwell some people want to share and keep lora
Fonly benefit it is
Fotherwise original checkpoint best
Fdont use captions
Fwhen you are training a single concept
Fif your concept is consisten, captions reduces likeliness
Fmy installers should work there
Fof course i assume python cuda cudnn are install
Fand nvidia drivers
Pso what should I use?
instance prompt and class only?
instance prompt and class only?
FPatreon
Get more from SECourses: FLUX, Tutorials, Guides, Resources, Training, Scripts on Patreon
Fyes
Fohwx + class
Pwhat about the outfit?
Pand even though the character is not accurate enough, I do find that my consistent captioning structure for the angle the character is standing and face expressions that are not the neutral ones works pretty well when I prompt for it
so should I caption those?
so should I caption those?
Por does it reduce likeness aswell
FFLUX uses image itself as embedding
Fso all is like auto captioned
Fi dont think you need to caption
Pand if the character is in a complex background, compared to some images with simple grey background, still not caption?
PIt seems like someone achieved great results and accuracy with captioning that looks like joy caption, and when he prompted for the example images, look at how short and simple the prompts are, and yet, with a very short trigger word he's generating Yasuke very accurately
https://civitai.com/models/459468/naoe-and-yasuke-assassins-creed-shadows-fluxponyxl?modelVersionId=919340
https://civitai.com/models/459468/naoe-and-yasuke-assassins-creed-shadows-fluxponyxl?modelVersionId=919340
PHow does one achieve this? this is what I'm trying to figure out
Peasy to use and high accuracy lora
Fwell if your background repeating
Fif you dont prompt background in inference
Fit will generate it
Fotherwise no issue
Fhave both characters in same image
Fwhile training
Fso it learns perfect both
Phe used
ss_learning_rate": 0.000002,
"ss_text_encoder_lr": 0.00005,
"ss_unet_lr": 0.00005
and
"ss_network_dim": "Dynamic",
"ss_network_alpha": "Dynamic",
what do you think about that?
ss_learning_rate": 0.000002,
"ss_text_encoder_lr": 0.00005,
"ss_unet_lr": 0.00005
and
"ss_network_dim": "Dynamic",
"ss_network_alpha": "Dynamic",
what do you think about that?
Phis lora file size is decent too 459mb, not too big
ATried MassedCompute and its working. I am trying to train LORA with 6 sample images 1024*1024, however the number of steps seems really high for 6 images; 12000. How do i reduce the number of steps, i am running 4x_GPU_Batch_Size_1 json
Fmake repeat 1
Fand if 4x gpu
Fmake epoch like 60
Fso it would be total 240 epochs
AYou mean this section
Fyes
AThank you, will update how it goes.
AIt says 14400 steps now 
Fyou are doing wrong
Fyou should watch vidoe without skip
Falso dont have sub folders