From original author:
SDXL can’t do armpit sweat pitstains or any sweat on shirt properly. This will fix it. It’s trained towards armpit stains, with less focus on chest, belly and back.
It had a lot of women on the trained data, it works regardless of gender.
This one took quite a lot of work even though it was a simple concept (low rank, low size). That is because I did an extensive epoch and block analysis. This one (and most non-pose LoRAs) benefits from a lower Text Encoder (base) weight and zeroing INS and MID blocks.
Recommended weight is 1.
Good from 0.8 up to 1.5 or further
I’m publishing this modified remerged LoRA as the main and not the full block one because people won’t f# read the best settings and Civitai generations don’t have these settings either way.
So, this is a remerge with these block weights: lbw=0.25,0,0,0,0,0,0.6,1,1,0,0,1 and also a re-scale from 1.2 to 0.8 using Ostris tool.
It should not change your original character or composition even at high weight. But you can lower the TE even further or even do a 0 weight TE if you want <lora:name:0.2:1>
This LoRA works at high weights. That is why I rescaled it. It has a low effect at 0.8, medium at 1.0 and high at 1.15. But you can go to 1.5 or more.
I only used trigger keywords to see if I could control the stains’ location, it doesn’t need them! They were not the first tag on the caption, but it helps to use.
I trained two LoRas and after block analysis they are both good. V5 uses “s3t”. Version 2 uses “sweat-spots-smudges”. I decided on V5 but sometimes V2 is better, especially with eyes.
Trigger Keyword:
V5: s3t on armpit, s3t on chest, s3t on belly, s3t on back V2: sweat-spots-smudges on armpit, sweat-spots-smudges on chest, sweat-spots-smudges on belly, sweat-spots-smudges on back
Supporting prompts:
Shirt; (shirt with sweat:1.3); wearing clothes; sweat-spots-smudges (can help V5 sometimes)
Negative supporting prompts:
Black dye, black paint, black smudges, blue paint, yellow paint, worst quality, jpeg artifacts, low-res
DON’T use the word “wet” as this token concept bleeds heavily in any model. You’ll get rain and water everywhere. This is not my LoRA problem, you should just not use this word unless that is what you want.
