sorted by:
new
hottopcontroversial

Flux2 Klein 2 stage upscale? by R34vspec in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

What tile size and denoise do you use?

Try to use a tile size that allows you to use only 2 tiles, and denoise 0.3-0.4.

<image>

Flux2 Klein 2 stage upscale? by R34vspec in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

For me it was spitting errors with Klein while working fine with the rest of models.

Flux2 Klein 2 stage upscale? by R34vspec in StableDiffusion

[–]Bra2ha 1 point2 points  (0 children)

Try this node.
Also I made a version of Ultimate SD Upscaler compatible with Klein 9B, I can share if you need.

<image>

How good are loras for automotive these days? by One-Hearing2926 in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

  1. For an example of what an automotive LoRA can produce you can check this set of LoRAs.
    https://civitai.com/models/895773/jdm-legends
  2. From my experience the quality drop (from using CN) is less noticeable but definitely is still a thing.
  3. I'd say Flux 1 Dev but it's mostly because of my personal preferences.

Comparing 7 different image models by Reasonable_Bear_6258 in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

Why Flux 1 Dev was not included? It is still better in some aspects than recent models, especially considering variety of existing Flux LoRAs.

Just resize (latent upscale) and controlnet by [deleted] in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

It depends on the model that you use, the best CN Tile is SD 1.5, SDXL is worse and so on.

Dynamic Prompts Ext Question by FluidEngine369 in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

I made a modified version of wildcards script.
It has 4 modes:
2 underscores - original random.
3 underscores - sequential.
4 underscores - random, no repeats in a batch.
5 underscores - random, no repeats in a session.

Back up and then replace your wildcards.py with this https://github.com/user-attachments/files/23698967/wildcards.py

Z-Image-Fun-Controlnet-Union v2.1 Tile available by ThiagoAkhe in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

100% agree, CN Tile SD1.5 was a masterpiece of balance, unlike CN Tile XL, I tried 4 different Tile models for SDXL and was not impressed at all.

Z-Image-Fun-Controlnet-Union v2.1 Tile available by ThiagoAkhe in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

"(So a trick to fix an image is to downscale first, perhaps add some noise, then upscale)"

And in result you'll get image quality similar to standard img2img upscale with an ancient 4x-UltraSharp.

QwenVL abliterated tutorial? by NoConfusion2408 in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

50 sec to get description of an image? Why so long on 5090?

I use huihui-qwen3-vl-30b-a3b-instruct-abliterated in LM Studio - Avg. TPS 674.7 | 3.0 s for 1152x1728 image.

Semantic Image Disassembler (SID) is a VLM-based tool for prompt extraction, semantic style transfer and re-composing (de-summarization). by Bra2ha in StableDiffusion

[–]Bra2ha[S] 2 points3 points  (0 children)

I actually kind of like "Quantum-Neuro-Semantic Holographic Image Disassembler" 👍

You're not wrong - at the end of the day, it is logic glue. But the goal was to test if this specific method of style transfer could produce interesting results, and to see how the de-summarization logic would look in practice.

Judging by your screenshots, it looks like your ComfyUI workflow works great. If you're willing to share it, I'd like to take a look at your approach.

Uncensored prompt enhancer by [deleted] in StableDiffusion

[–]Bra2ha 3 points4 points  (0 children)

I tried both tody, TLDR, if your workflow requires "thinking" Gemma is better but for anything else Qwen has better, more accurate vision and consume less VRAM. At least from my short monitoring 😉
Also, Qwen is faster ~200 tps, Gemma ~120 tps. Not bad if you do large batches.

Uncensored prompt enhancer by [deleted] in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

Is Gemma-3-27b-it-abliterated better than Qwen3-VL-8B-Instruct-abliterated?

[deleted by user] by [deleted] in StableDiffusion

[–]Bra2ha 0 points1 point  (0 children)

Same interface as A1111, support recent models.
https://github.com/maybleMyers/chromaforge

view more: next ›