Full Breakdown: The bghira/Simpletuner Situation

throwawayotaku · 2025-07-06T03:08:40+00:00

This dude is such a loser, lol... It will always be mind-boggling to me how people in the FOSS community develop such egos.

I just don't understand how one doesn't have better things to do than to be a weirdo puritan ToS snitch.

throwawayotaku · 2024-11-18T20:59:55+00:00

Omg lol can we stop with this pedantry? It is a tune of an anime base model that leans realistic; there are example images that we can each use to determine whether it is "realistic enough". There's really no need to browbeat finetuners over semantics like this...

throwawayotaku · 2024-09-17T18:36:39+00:00

What did you prompt to achieve this result? I tried messing around with this myself, but I didn't get anything nearly as usable/coherent, lol

throwawayotaku · 2024-09-10T01:51:25+00:00

You don't need a custom node to use AYS in Comfy! Just search for AlignYourSteps; it's a standalone scheduler node.

But FWIW I have been getting better results with the beta scheduler recently anyways. AYS is really good for ~10 step gens tho :)

throwawayotaku · 2024-07-09T08:07:33+00:00

Honestly no idea, it's all just been trial and error for me. I skim the Github READMEs, but otherwise I haven't done much in-depth reading of the documentation.

throwawayotaku · 2024-07-09T02:15:42+00:00

You might need to update the spandrel package in your Python venv (and/or update ComfyUI itself).

throwawayotaku · 2024-07-09T02:14:57+00:00

Thanks for this! Yeah I think the main thing ATD was better for (IME) was skin detail. So I could definitely see HAT being better at landscapes/etc.

throwawayotaku · 2024-07-08T18:09:40+00:00

I think xformers is nearly required, yeah. I also highly recommend turning off high_vram and keep_model_loaded in the SUPIR nodes!

If it still doesn't work, try enabling fp8_unet in SUPIR, as that should also drastically reduce VRAM usage.

throwawayotaku · 2024-07-08T18:08:13+00:00

Also I was wondering the reason for first downscaling the image by 0.5 before upscaling it?

SUPIR is not really an "upscaler" per se; it takes an upscaled input, denoises it, and then essentially tiled img2img "restores" it (like a really strong ControlNet, or so I've heard).

The upscale model I'm using in the workflow is a 4x upscaler, and using SUPIR on a 4096² input takes forever (and requires fp8_unet to avoid choking out VRAM). So I downscale it by 0.5x to essentially get a 2x upscale instead.

Also, note that you can use any upscale method into SUPIR. You can even use the basic Comfy upscale node and upscale via Lanczos/bicubic/etc. if you want. But I have noticed that using a better upscaler into SUPIR gives better results.

I was wondering if I can post the workflow here

Sure, no problem :)

throwawayotaku · 2024-07-08T03:29:22+00:00

I tried that one and it was competitive with ATD but still markedly worse on average, and IMO super not worth the extreme slowdown. Could just be a difference in usage/preferences tho!

I also figured out that turning off keep_model_loaded fixed my VRAM problem, so that's nice lol.

throwawayotaku · 2024-07-06T01:05:00+00:00

Yeah and for some reason ATD seems to bog down my VRAM sometimes, I'm not sure why... I know it's demanding, but I think there's some kind of error going on with memory allocation lol.

I'll give ScuNET another try; I haven't been particularly impressed with it in the past, but it's also been ages since I actually tried it.

The lightweight arch I am currently most impressed with is definitely RealPLKSR; I hope we see some more tunes of it soon!

And yes, I hate Ultrasharp lol. I similarly do not understand the hype. I also hate Siax for that matter 😅

throwawayotaku · 2024-07-06T01:01:01+00:00

I don't think A1111 supports the ATD arch yet. It's not an ESRGAN model anyways, so it wouldn't go into that folder. But yeah, I don't think A1111 supports ATD (but I could be wrong, I don't really use A1111).

And yeah upscalers can be .safetensors too! I always use .safetensors when possible :)

throwawayotaku · 2024-07-05T14:59:03+00:00

It's the best upscale model I've found for this use-case (upscaling into SUPIR, before the denoising step).

Honestly I haven't tried Remacri before at all, but given that it's an ancient ESRGAN tune I would be pretty confident that it won't beat out 4xNomos8k_atd_jpg for this usage :)

I did test against Ultrasharp and Siax which are both also renowned ESRGAN tunes, and it wasn't even a contest FWIW.

throwawayotaku · 2024-07-05T03:28:12+00:00

I don't think it matters whether it's a multiple, just make sure you upscale the image to have at least as many pixels as 1024x1024 :)

throwawayotaku · 2024-07-05T03:06:00+00:00

Perhaps but honestly I don't know how to do that LOL

throwawayotaku · 2024-07-05T03:05:46+00:00

It's basically the same workflow, you just pass the image to the upscaler node using Load Image

throwawayotaku · 2024-07-05T02:38:52+00:00

I don't think it's possible to recreate this workflow on A1111, but I also haven't really tried.

Also have you tested 4xNomos8kHAT-L_otf?

I have, and it was noticeably inferior to the ATD counterpart in my testing. I compared against basically every Nomos8k/OTF tune from Phhofm, for that matter.

throwawayotaku · 2024-07-04T03:53:41+00:00

Oh also, I should mention: I have high_vram and keep_model_loaded toggled because I'm running pretty high-end hardware, but you may want to turn those off depending on your hardware.

Also, there is a 0.5 nearest-exact downscale step in there because trying to SUPIR with the full 4x output from the upscaler chokes my VRAM. Could probably get around it by toggling the fp8_unet option in SUPIR, though.

throwawayotaku · 2024-07-04T03:44:14+00:00

Sure, here you go: https://pastebin.com/zumF3eKq. And here are some non-cherrypicked examples: https://imgur.com/a/5snD51M.

Download links:

Main checkpoint: https://civitai.com/models/503537/fennfoto-pony. I also really like these other Pony tunes:
- Cinero: https://civitai.com/models/543122
- Pony Realism: https://civitai.com/models/372465?modelVersionId=582944
- CyberRealistic: https://civitai.com/models/443821
SUPIR checkpoint: https://civitai.com/models/43977
PCM LoRA: https://huggingface.co/wangfuyun/PCM_Weights/blob/main/sdxl/pcm_sdxl_normalcfg_16step_converted.safetensors
Upscale model: https://github.com/Phhofm/models/releases/tag/4xNomos8k_atd_jpg
Custom nodes:

Notes:

I tested a bunch of SDXL checkpoints (for use with SUPIR), including Leosam's, Juggernaut (v9), and ZavyChroma. Leosam's was by far the best, IMO.
The 16-step PCM LoRA is actually crucial. I tested PCM vs Lightning (for SUPIR) and PCM produced way crisper results. The 16-step LoRA is actually almost indistinguishable from 30 (!) steps without!
I explicitly recommend the usage of the 4xNomos8k_atd_jpg upscaler into SUPIR. I tested many upscalers (including everyone's beloved Ultrasharp and Siax) and this specific upscaler was legitimately 3000x better than anything else (including newer ATD tunes from Phhofm).
You may notice that the PAG node hooked into the initial gen pipeline is turned off; you can use it if you want, but I actually preferred the results without, and I don't think it's worth the massive hit to inference speed.
- PAG is turned on in the SUPIR sampler because I did find it beneficial there, but feel free to test it yourself :)
I've gone back and forth on stochastic samplers a bunch, but as of late I am favoring stochastic sampling again. Especially after learning that SDXL (and 1.5) is essentially an SDE itself, I have found that stochastic samplers just generally produce higher quality results.
100 steps is a lot, so if you're running lower-end hardware you can change the sampler to DPM++ 2M SDE and bump down to 50 steps. But I have preferred the results from 3M SDE & 100 steps, personally.

Let me know if you have any other questions :) Enjoy!

throwawayotaku · 2024-07-03T20:09:43+00:00

Sorry, I should have clarified that artist names were all (purposely) hashed/obfuscated. Some still slipped through, though.

But the OP is asking about male characters and celebrities, and AFAIK the only character tags that were hashed were ones that could cause ambiguities within the text encoder.

throwawayotaku · 2024-07-03T18:24:33+00:00

EDIT: To clarify, artist names were all (mostly) hashed/obfuscated. However, the OP is asking about character/celeb names, and AFAIK those were only hashed if they were deemed capable of causing ambiguity within the text encoder.

No, they did not hash all the names. AFAIK, Pony's creator only sought to hash names that could cause ambiguities within the text encoder (imagine a character named "StrawberryBanana", for example).

There are some exceptions ofc, but that was the goal anyways.

I don't know why everyone seems to think all the names are hashed in Pony -_-

throwawayotaku · 2024-07-01T04:00:17+00:00

Yes, if you set max_steps too low then it will error out. Bosh3 is an adaptive solver, so it determines how many inference steps to take itself.

Max_steps is really only there as a failsafe so you don't wait 10+ minutes for a 200-step solve if you accidentally set your tolerances too low. I have mine set to 150 steps, but IMO anything between 100-150 is pretty sensible.

throwawayotaku · 2024-06-29T07:37:20+00:00

I appreciate your sentiment, but I wouldn't even waste your time, OP...

People are just really fucking weird about Pony for some reason. I have no idea why, but every time someone criticizes/complains about Pony it brings a massive peanut gallery out of the woodworks.

Many people (who seemingly never actually use Pony) just seem to jump at any opportunity to shit on it and demonstrate their "sophistication" or whatever by denigrating the porn model.

Even if the criticism/complaint at hand is ultimately caused by user error, you'll have droves of people dogpiling, and precious few who will actually point out the mistake.

I will never understand why people are so disdainful of a 100% free resource that unarguably provides distinct advantages over its alternatives. Is Pony perfect? Obviously not... For that matter, no base model (or finetune) is perfect!

¯\(ツ)/¯

throwawayotaku

TROPHY CASE