Neta Lumina Lightning LoRA
All cover images are raw output from the model, 1MP resolution, no upscale, no hands/faces inpainting fixes, even no negative prompt.
What is this
This is CFG distilled Neta Lumina, and is trained as LoRA natively.
2x faster.
Currently support:
NetaYume Lumina (NTYM)
About CFG distilled model:
You can't control CFG scale and negative prompt. Those are trained inside the model.
Built-in artist styles are weaker. Because artist styles have the highest variance.
Other kinds of penalty (concept etc.) are unnoticeable. Unlike step distillation (4/8 steps model etc.), CFG distillation is simple and not aggressive.
Interesting pros:
Noticeably better hands and limbs.
Stronger and more accurate (?) style from style LoRA.
Don't know why. I assume that distilled model has less "noise and outliers", so overall it's more "stable".
How to use
Required settings to work:
LoRA strength 1
CFG scale 1 (This disables CFG, and negative prompt)
Do not use cfg++ (cfg_pp) samplers, they do not work.
Recommended settings:
Timesteps shift 3 (from node ModelSamplingAuraFlow)
Steps 20. If you really just want to test something (concept etc.) very quickly, 12 steps is also doable.
Sampler: euler/euler_a + normal
License
This model is released under Apache License 2.0.
Additional terms: Selling or monetizing models that merged this LoRA is prohibited.
Update logs
I may release multiple sub versions (abcde...), with different CFG (maybe different negative prompt too). So you can choose the CFG you want by choosing LoRA.
If you want to share your images, please post them to the main version page (a).
v1.0 (11/21/2025):
Mimics the effect of CFG 5.
Finally, found and fixed a noise mismatch issue in all v0.2 versions. What the f is the "renorm_cfg" thing in official Lumina 2 code.
Also skipped early layers which have extremely large activation values. Should have better compatibility with other LoRAs.
v0.2: Init version, experimental.
v0.2a: Init version. mimics the effect of CFG 3.5.
v0.2b: This version mimics the effect of CFG 5.
v0.2c: This version mimics CFG 4. Also added some normalizations on mean and variance of noise the teacher model predicted, balabala...
Still experimental, can't say which version is better. Try yourself.
You have read this far, don't forget to leave a feedback in discussion. Don't write a review, Civitai review system is so hard to find and, most importantly, read...
Description
FAQ
Comments (3)
Not enough versions! Make and upload 50 versions I will never download, pls
I tried using it a little, and found that the combination of the gradient_estimation sampler and beta scheduler produced good results even with 10 to 15 steps. Since 10 steps can lead to rough details depending on the seed value, the sweet spot when using the gradient_estimation scheduler seems to be somewhere between 11 and 15 steps.
P.S. For me,I felt that steps 11 to 12 were of a fairly satisfactory quality.
it certainly makes it faster, but I find it doesn't really follow style instructions anymore, it's funny it makes hands and limbs better but I find faces and eyes worse lol (im using the b version), I've tried it with res_multistep, euler, euler a, and with beta/normal/linear_quadratic/simple
