Taking Krea-2 apart, one piece at a time
I wanted to investigate if nudging the weights of single blocks of Krea-2 can teach us something about its internal structure.
Proof1 community thread
Key points
- Hellow fellow AI-generated goblins of r/StableDiffusion
- For a few weeks I’ve been stress-testing my tool, Arthemy Krea-2 Tuner:
- I worked on two parts: the model and the text encoder (I only started on the last one recently but it seems much more interesting than the previous one).
- It’s still sci-fi at this point, but if we manage to map the inside of a model this way, we might be able to make presets that do the job of a small fine-tune with nothing trained: the presets I use now are 34 numbers, a few hundred bytes, against the tens or hundreds of MB of a typical LoRA.
Sources (1)
- [1]Taking Krea-2 apart, one piece at a timer/StableDiffusion (top, day) · Oct 14, 04:32 PM
I wanted to investigate if nudging the weights of single blocks of Krea-2 can teach us something about its internal structure.
Hellow fellow AI-generated goblins of r/StableDiffusion
Extractive summary: sentences quoted from the sources.
Before this
- Oct 14, 2026GPT-Image-style photo editing on your own GPU (12 GB+): I built a zero-setup app for Qwen-Image 2.1 on stable-diffusion.cpp
- Oct 14, 2026ReGRA: Residual-Gradient Adaptation for Complementary Low-Rank Fine-Tuning
- Oct 14, 2026Train LoRA directly on Quantized GGUFs, no PyTorch, no Parent(FP16) needed, just your GGUF and the data
- Oct 13, 2026Comfy-Org/ComfyUI v0.40.0
- Oct 13, 2026Gausify Orbit is now open source: turn AI-generated 360 orbit videos into Gaussian Splats, entirely in your browser
- Oct 13, 2026DT-LoRA: Reaching Beyond the Tangent Space of Low-Rank Adaptation