from experience I can tell you that the cosmos-dmd LoRA is good for mixing with the others


so the real User Preferred Speed Distillation setup is some bizarre mix of them all :' )

I love RDBT, but I hate how bad it is with styles. If the prompt is somewhat short like 30 tokens, it basically ignores the artist tag completely, and it seems even more prone to do so if you prompt something that is NSFW. But even with longer prompts it's still a major issue, aswell as things just looking very washed out.

Maybe it would look a lot more faithful to style if I went crazy like 1000 tokens or something, but I shouldn't have to just for the sake of getting the style I want. I have no idea why RDBT does this when style is basically the most important factor when genning.

It's still quite fun to use if you don't care about style and want something that looks more visually pleasing (other than washed out colors) faster with what appears to be a bit better quality.

I might use it every now and then for casual fun SFW memes or cute stuff. But the instability is just insane. I had a relatively simple prompt where it had "photorealistic" tag and it worked as expected, then I add in a couple NSFW tags and boom, SD1.5 style lol.

Now if only anima could do some basic furry concepts. I really hope they decide to include E621 into the training data, or at least make another version with it in.

There's so much damn potential with Anima, and to think we're only at a preview version, not a finished model or a finetune of the finished model.

Almost the same

CFG 1.1 will probably work fine and allow negative prompts. You could also try NAG or one of the other no cfg negative methods.

There's Normalized Attention Guidance, NegPiP (in comfyui-ppm), or making your own silly setup by running the turbo LoRA at a lower strength and compensating with https://civitai.com/models/2364703?modelVersionId=2684678
some portion of "anima_preview_rdbt_v0.6_cfg_distilled_only" on top

@VeerGeer Tried NegPip, 'Anima' object has no attribute 'text_processing_engine

@VeerGeer "Normalized Attention Guidance" don't work for Anima

@chaosleges sounds like the text encoder isn't being loaded in as expected

https://civitai.com/images/128368192
a workflow with it working looks like that, at least with the nodes from this repository;
https://github.com/pamparamm/ComfyUI-ppm

I'm using this one: https://civitai.red/models/2426853/anima-preview-workflow

Could you share your workflow ?

Same here, less details, less color, sometimes limbs are not complete but significantly faster gen speeds. Hands on hip, but no forearm just floating wrist and palm on hip. CFG1, 12Steps.

Had i started with turbo i would have been satisfied but after experiencing what Anima is capable of, I'm just too spoiled to be satisfied with turbo. Perhaps I'm doing something wrong, perhaps its just what it is.

The hands looking good is a result of high accuracy on anima, this basically gives anima a mini version that is trying to replicate anima in the lightest way possible, instead of using all the data in the big model. This makes it less complex, which means it takes less steps to be more accurate. This comes at the cost of the model needing to essentially listen to itself more than it listens to your prompt, and thus being less capable at creating more complex, abstract concepts that aren't common in the data the model was trained on.

@CocoLarge Ohhh... I... still don't know if I get it. So the smushing of the Turbo lora into fewer steps results in better consistency, at the cost of constrained creativity? So it's a choice between more complex generations that allow for errors, or more rudimentary ones that don't do anything that might result in errors?

@Derpression Not exactly. Because the turbo lora makes the model want to reach a final image quickly by simplifying data, rushing towards the training data and then asking itself if the final image looks like the training data. This method of asking itself if the image looks like the training data conflicts with cfg and can cause problems. Which is why the instructions for turbo/lightning/dmd2 ask for you to use cfg 1 (cfg 1 is equal to not having cfg turned on). The problem is, cfg helps the model follow your prompt more closely. Errors aren't really a part of this equation. Errors can either be a thing that just happens randomly, or the result of not having enough steps (aka low accuracy).

The simplifying of the data results in the model knowing less.

Yes unless you use NAG (Normalized Attention Guidance): https://github.com/BigStationW/ComfyUI-NAG-Extended/tree/main

@AnimaXx i guess the workflow that im currently using might be a challenge for me to edit the nodes, rip. . .

You can set it to 1.5, and it will still work and look largely the same (although, from what I understand, long negative prompts might not work reliably?). If some parts of your negatives still get ignored, pushing it up to 2.0 might help. Beyond that, you might start noticing some fried contrast.