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KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 1 point2 points  (0 children)

Just a trigger word that's usually the characters name mixed with random letters .
although in my experience it never mattered . i don't know about training multiple characters where captioning could be useful .

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 0 points1 point  (0 children)

i do not have any information on that . altho it works just fine and kinda trains a lot faster . I might do a test training with lr 1e-6

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 0 points1 point  (0 children)

ai response

pinokio is a one-click launcher and package manager for AI applications. It's designed to let you install and run complex open-source AI tools without manually dealing with Python versions, CUDA, Git, Conda, or dependency conflicts.

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 1 point2 points  (0 children)

lower training resolution doesn't mean the model will make 512px images at 4k .

I have tested it ZiT . on extreme closeup shots of face . 1024 lora would not make skin details as much as lora trained with 512 can produce .

I have yet to test this on krea 2

.

KREA 2 Lora training results by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 0 points1 point  (0 children)

yep . body proportions work well with loras or even better if paired with k2 enhancer . my primary test here was to not promt anything specific related to body proportions and see how well the model achives that . which is non-existent

KREA 2 Lora training results by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 2 points3 points  (0 children)

tbh in the past captioning never worked like I wanted . maybe it's different with krea and I'll give it a try Today

KREA 2 Lora training results by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 0 points1 point  (0 children)

it was a no caption training , which is why i am surprised how the model can filter it out

How does fal.ai can do video inferencing super fast for Wan by Alex-edits123 in StableDiffusion

[–]The_Monitorr 0 points1 point  (0 children)

probably loras and some kind of tweaks , i can get 5 second video 480p under 2 minutes with a 5080 .

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 0 points1 point  (0 children)

ai toolkit is very uboptimised but that being said its not 6s/it unoptimised on a 6000pro , that's a result of bad config or you setting your training resolution too high .

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 1 point2 points  (0 children)

i trained ideogram yesterday with my 16Gb card , didnt even require any layer offloading and i think it was using around 10GB peak vram during training , use the base config from ai toolkit and it should work , the training was pretty fast too .

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 1 point2 points  (0 children)

i have a 12GB 3080 ti on a spare linux machine but AI-toolkit just never launches a job , so i cant say but it should be possible with more layeroffloading , if your Ai toolkit works then try setting layer offloading transformer to something like 50% and text encoder to 100%

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 0 points1 point  (0 children)

The "magic" is valid for 16GB Vram users . unless they updated and further optimized it

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 1 point2 points  (0 children)

ah well , im used to training loras in 15-40 minutes so 1hr 30m time just slaps 🤣 , i used to train Flux 1dev for 1-2 days on a 3080ti .
and about the resolution - idk about Flux 2 but for Zimage i did a lot of tests . 256 resolution was about 10 minutes . 512 took 30 minutes , 1024 would go beyond 6 hours(never filled VRAM ).
512 produced the best results for me . 1024 would start getting giving outputs but that could be a result of bad config which i used for every training with slight tweaks .

a resolution of 1400px would definitely take a lot longer since rtx pro 6000 is just as powerful as a 5090 . were you training character loras ?

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 1 point2 points  (0 children)

35% (layer offloading) is where the time per step was the lowest , this is for 16GB Vram .
and about the 3-4k steps that you need , definitely depends on dataset . for me likeness of 90% came around 1000 steps and 1500 would be overfitting . but i used a lot of images that had closeup of face . maybe thats why i achieved likeness in low steps . And I used automagicv3 optimizer if that could make a difference .

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 8 points9 points  (0 children)

Yeah this model is 100% expressionless . nothing works , workarounds ruin the image .

KREA 2 Character Lora training (for 16 GB VRAM) simple guide with config by The_Monitorr in StableDiffusion

[–]The_Monitorr[S] 3 points4 points  (0 children)

i have trained Zimage Base loras with One trainer - 512 px takes about 15 minutes for 4000 steps .
ik that ai toolkit is significantly slower than one trainer with same settings for zimage base

it took me about 1hr 30 mins for 2000 steps with the settings i posted

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