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Official repository for "CFG++: manifold-constrained classifier free guidance for diffusion models"

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I just tried your example of editing on the README, literally ``` python -m examples.inversion --prompt "a photography of baby fox" --method "ddim_inversion_cfg++" --cfg_guidance 0.6 ``` but I get nonsensical...

Hi, First, congratulation on your paper, it looks very promising. Do you have an idea/intuition on if it would work for the EDM framework? Thanks in advance.

i want to change generation size from 512 x 512 to 768x768 which one should i change on latent_diffusion.py??

need colab demo example that can change model checkpoint for sd3

Can you improves support for Regional Prompter with multiple loras used? Using [Forge Couple](https://github.com/Haoming02/sd-forge-couple) or [sd-webui-regional-prompter](https://github.com/hako-mikan/sd-webui-regional-prompter) (Attention mode) with [CFG++](https://github.com/CFGpp-diffusion/CFGpp) crossover details with between characters more then the other sampling...

https://github.com/CFGpp-diffusion/CFGpp/blob/3a6655dc9348ee544bc33956dc55d7d63ada2823/examples/inversion.py#L11 https://github.com/CFGpp-diffusion/CFGpp/blob/3a6655dc9348ee544bc33956dc55d7d63ada2823/examples/inversion.py#L39-L55 The `--model` argument is set to `sdxl`, but `get_solver_sdxl` is not being used, so SD1.5 is executed instead of SDXL.

I tried to implement this for flow models as described in the appendix, but the results are complete collapse (exploding images). Did I make a mistake or is this technique...

I'm confused about the transition of CFG to CFG++ in some sampler cases. Some samplers, such as iPNDM, extend euler and do the noise combination based on ODE/SDE or other...

Thank you very much for your work. I would like to know what command you used to test the experimental results. The results of my tests always have some issues.