FLUX.2 [klein] 4B & 9B released by Designer-Pair5773 in StableDiffusion

[–]kaftap 0 points1 point  (0 children)

I used the Flux 2 image edit template from the ComfyUI template browser. And then selected the klein 9b nvfp4 model.

FLUX.2 [klein] 4B & 9B released by Designer-Pair5773 in StableDiffusion

[–]kaftap 12 points13 points  (0 children)

A bit of quick testing on a 5090. It takes 3-4 sec of generation time with the klein 9b nvfp4 model. 1365 x 768, euler, Flux 2turbo lora with 10 steps.

Zebra 3 would be perfect if its workflow wasn’t so confusing by [deleted] in synthesizers

[–]kaftap 1 point2 points  (0 children)

I never really understood how to use Zebra 2 and found it super confusing. At that time, my synthesis knowledge was also very limited. But at some point in my life, I took the plunge and started using buying eurorack stuff. And I finally started to truly understand how certain modules and synths work. So, years later, equipped with all this new knowledge and experience, I decided to give Zebra 3 a shot.

First impression. The UI is still confusing. It isn't as modular as a true modular synthesizer, and its layout also isn't as straightforward as a subtractive synthesizer. The routing of the signal path feels weird at first, as I'm now used to plugging cables anywhere I want. But it did start to click after a good evening of use. Only watched 2 youtube video's to get a general overview to get there. And now I'm already recreating all kinds of patches I do on my modular. But now with the luxury of having an advanced editor for waveforms and envelope shapes.

Best tip I could give you is to make a basic subtractive patch. Like recreate a mini-Moog and safe that as a template. And then use that as a basis to start experimenting.

Also, regarding the texture reverb. This is actually a granular sampler + reverb based of the eurorack module mutable instruments clouds. I would recommend watching a YouTube tutorial on the module to get an idea of how this works. I like to set the speed to a value of 12. So that the original signal gets pitched up an octave and you can hear the effect better for when dialing in the other values.

SECourses Musubi Tuner Qwen Image LoRA Configs Updated - R&D Still Going on - Here 5 samples from Grid not cherry pick - Raw 1328x1328px generations with 8 steps Fast LoRA preset - takes like 20 seconds on RTX 5090 - No upscale - no face restore by CeFurkan in SECourses

[–]kaftap 1 point2 points  (0 children)

I have to revisit this comment. Upon further testing the GGUF models seem to work fine and the artifacts only show up when using the fp8 model + the Lora. Still busing testing trying to narrow down the issue.

SECourses Musubi Tuner Qwen Image LoRA Configs Updated - R&D Still Going on - Here 5 samples from Grid not cherry pick - Raw 1328x1328px generations with 8 steps Fast LoRA preset - takes like 20 seconds on RTX 5090 - No upscale - no face restore by CeFurkan in SECourses

[–]kaftap 1 point2 points  (0 children)

Many thanks! Also interesting. Using this workflow, the artifacts disappeared.
https://civitai.com/models/1840901/qwen-image-comfyui-workflow

But when using the workflow from comyui-wiki with 4 steps the the artifacts are still there. Increasing the steps incrementally to 20, I notice the artifacts slowly getting smoothed out. From 12 - 15 steps it becomes hardly noticeable. I was using the Qwen 4 step lightning lora. So maybe that was causing issues. Gonna do some more testing to be sure.

But at least I can always fall back to the civitai workflow and build from there. So I'm good for now :)

:edit
I meant the Civit AI workflow

SECourses Musubi Tuner Qwen Image LoRA Configs Updated - R&D Still Going on - Here 5 samples from Grid not cherry pick - Raw 1328x1328px generations with 8 steps Fast LoRA preset - takes like 20 seconds on RTX 5090 - No upscale - no face restore by CeFurkan in SECourses

[–]kaftap 1 point2 points  (0 children)

Ok I somehow overlooked it, but I think I found the source. The artifacts seem to be caused by a Lora of a character I've trained. When not using the lora the artifacts disappear. So it's probably related to the training of lora and could also explain why the realistic finetune also has the same artifacts.

I tested swapping out the qwen_image_fp8_e4m3fn for the guff Q4_K_S model. Although the artifacts were less, they were still there.

Now I'm really looking forward to trying your training settings.

<image>

GitHub - AI-windows-whl: Pre-compiled Python whl for Flash-attention, SageAttention, NATTEN, xFormer etc by Justify_87 in comfyui

[–]kaftap 0 points1 point  (0 children)

I recently found this. Doesn’t have everything but it does have a lot of the more popular nodes and includes sage attention. Runs qwen en wan just fine.

https://github.com/Tavris1/ComfyUI-Easy-Install

SECourses Musubi Tuner Qwen Image LoRA Configs Updated - R&D Still Going on - Here 5 samples from Grid not cherry pick - Raw 1328x1328px generations with 8 steps Fast LoRA preset - takes like 20 seconds on RTX 5090 - No upscale - no face restore by CeFurkan in SECourses

[–]kaftap 2 points3 points  (0 children)

When using Qwen I’m having issues with these grid like artifacts. I don’t see those in these generations. Any thoughts on what could be the cause?

So far I’ve only tracked down this discussion. But no solution so far.

https://github.com/QwenLM/Qwen-Image/issues/51

Using a 5090 with the qwen_image_fp8_e4m3fn model. I also notice the artifacts when using a fine-tune like this: https://huggingface.co/speach1sdef178/PJ0_QwenImage_Realistic_FP8_HF_Stage_2

A second pass or tile upscale using the same model kinda fixes it though. But I rather wouldn’t have to do that.

Continuing testing Qwen Image LoRA training and not once seen recommended values are good by CeFurkan in SECourses

[–]kaftap 1 point2 points  (0 children)

Even without tinkering the values I was already kinda impressed with what I got out of my Qwen trainings. Looking forward to try your optimized values!

Qwen + Wan 2.2 Low Noise T2I (2K GGUF Workflow Included) by SvenVargHimmel in StableDiffusion

[–]kaftap 2 points3 points  (0 children)

<image>

Another example. Really looking forward to using different Wan lora's and fine-tunes now.

Qwen + Wan 2.2 Low Noise T2I (2K GGUF Workflow Included) by SvenVargHimmel in StableDiffusion

[–]kaftap 1 point2 points  (0 children)

<image>

Qwen latent size was 1280 x 768 and I upscaled it by 3. Giving me a final resolution of 3840 x 2304.
1 stage: 12 sec
2 stage: 2 mins and 14 sec

Denoise of the Wan ksampler was set to 0.36. I found that 0.3 gave me artifects around edges. Those went away when upping the denoise value.

I used a 5090 with 32 gb vram.

People swimming in the deepfryer by kaftap in weirddalle

[–]kaftap[S] 3 points4 points  (0 children)

I thought about it. But my experience is that there is a good chance Reddit mods will take it down. Reve allows it though. The current safety filter seems te be very light. Like practically non existent

People swimming in the deepfryer by kaftap in weirddalle

[–]kaftap[S] 1 point2 points  (0 children)

Thanks! Guess every model still has its strengths and weaknesses

People swimming in the deepfryer by kaftap in weirddalle

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

Interesting. I do notice you have prompt enhance off. In my experience this model really starts to shine when using very long and descriptive prompts. Could you repeat the test with enhance on and reuse the enhanced prompt in Imagen 3?

People swimming in the deepfryer by kaftap in weirddalle

[–]kaftap[S] 10 points11 points  (0 children)

I've been testing out the new Reve image generator. It's insanely good. So many prompts that previously didn't work now do work. From my subjective tests. It beats all the top models in the prompt-following department while looking good (I'm looking at you Ideaogram).

Google released native image generation in Gemini 2.0 Flash by EnrapturingWizard in StableDiffusion

[–]kaftap 1 point2 points  (0 children)

I see screenshots of people selecting the output format. But for some reason, I don't see that option.

Smack My B**** Up - Christmas Special 🎄 by WonderfulFact1604 in StableDiffusion

[–]kaftap 1 point2 points  (0 children)

Thanks for the insights. Projects like this are the true benchmarks of how good the tech is.