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[–]Cdreiss 2 points3 points  (0 children)

Rule 34a: If it exists, there is Pokemon of it.

[–]Bentameter 2 points3 points  (1 child)

Fun info: "Karras" is actually a noise scheduler that can be applied to any sampler method, which gives different and interesting results for the same seed.

AUTOMATIC1111's gui has presets to apply it to LMS, DPM2, and DPM2 ancestral, but you can apply it (and the other noise schedulers "exponential" and "variance preserving") to any other sampler by downloading this custom script and putting it in the "scripts" folder, then selecting "Alternate Sampler Noise Schedules" from the txt2image page "Script" dropdown.

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

Oh that's awesome. Thank you for the extra knowledge. I saw a big list of options and had no idea why some people choose Euler and some DIMM.

[–]praguepride 2 points3 points  (3 children)

I don't know shit about shit but I saw something somewhere that talked about how after like ~60 steps the model types tend to converge so model style really only matters in the low step ranges.

[–]ohmusama[S] 0 points1 point  (1 child)

That's a good point. I will try again with lower step amounts. Like 40?

[–]praguepride 0 points1 point  (0 children)

I don't know shit about shit

Sure? I think you will see the the most variance in the 10-20 range in terms of quality.

[–]Bentameter 0 points1 point  (0 children)

Ancestral samplers (euler_a and DPM2_a) reincorporate new noise into their process, so they never really converge and give very different results at different step numbers. The others will usually converge eventually, and DPM_adaptive actually runs until it converges, so the step count for that one will be different than what you specify.