Type | |
Stats | 1,153 12,834 2.9k |
Reviews | (179) |
Published | Apr 29, 2025 |
Base Model | |
Usage Tips | Strength: 0.2 |
Hash | AutoV2 F5F09FD929 |
Contrast Controller
Control contrast in SDXL just like using a slider on your monitor. Stable, linear, and has zero side effect on style.
Or an U-net output strength regulator, if you know what I am saying.
What does this LoRA do?
It can amplify (strength >0) or reduce (strength <0) the contrast of your base model.
400KiB LoRA file? WTF Is the file broken?
No. It is a fully functional LoRA.
How to use it?
Just apply it as normal LoRA.
If you want to enhance the contrast, recommend to set strength 0.2 and forget. Also recommend lower your CFG scale a little bit for better details.
Working strength is around -0.5~0.5.
You don't have to set the patch strength for text encoder. This LoRA does not patch it.
Supported models?
All Illustrious based models, including NoobAI e-pred, are guaranteed to work. Unless your base model somehow changed U-net OUT8 block, which is very rare.
Other models (like v-pred) maybe work, I just did not check and test.
What's the training data? Why zero side effect on style?
This LoRA does not come from training.
I know how stable diffusion works. There is no contrast. What you said above is BS.
Yes it is BS, so to speak. Because it's simple for most of users to understand.
Here is the description for advance gigachad users:
You may have heard about FreeU. It can manipulate U-net blocks output. But it requires software support. What about using LoRA to do the thing?
So you can think of this LoRA as FreeU, sort of. It manipulates U-net output, mainly in strength.
You no longer have to choose between "creativity/low CFG scale" and "high contrast". Now you can have both.
You can increase unet strength so you can lower CFG scale, and get more creative result and details.
Or vice versa, reduce unet strength so you can use higher CFG to get a stable and clean result, without oversaturation.
Share merges using this LoRA is allowed. However, you must credit the creator and provide a link to this page. Beware that weight pattern will become very unique after this LoRA applied. A normally trained model will never have such kind of pattern.
This LoRA is highly experimental. Remember to leave feedback in comment section. Don't write feedback in Civitai review system, it was poorly designed, literally nobody can find and see the review.
Have fun.