"Native refiner swap inside one single k-sampler. The advantage is that now the refiner model can reuse the base model's momentum (or ODE's history parameters) collected from k-sampling to achieve more coherent sampling. In Automatic1111's high-res fix and ComfyUI's node system, the base model and refiner use two independent k-samplers, which means the momentum is largely wasted, and the sampling continuity is broken. Fooocus uses its own advanced k-diffusion sampling that ensures seamless, native, and continuous swap in a refiner setup."<p>This is so interesting and seems obvious in retrospect, but super impressive! The code is simple too, going to hack around with this over the weekend :)
> Linux and Mac<p>> Coming soon ...<p>Ah well. Hopefully it is soon. Also, on behalf of all Apple Silicon Mac users, would be nice if the author looked into implementing Metal FlashAttention [1].<p>1. <a href="https://github.com/philipturner/metal-flash-attention">https://github.com/philipturner/metal-flash-attention</a>
For those who don't know, ControlNet is often used in conjunction with Stable Diffusion. It lets you add extra conditions to guide what is being generated. There are extensions for Automatic1111's stable diffusion webui that can make use of ControlNet. Some examples I've seen are copying the pose of a person/animal in an image and outputting a different person with the same pose (and extending to videos). Also taking line art drawings and filling it in with style.<p><a href="https://stable-diffusion-art.com/controlnet/" rel="nofollow noreferrer">https://stable-diffusion-art.com/controlnet/</a>
> Learned from Midjourney, the manual tweaking is not needed, and users only need to focus on the prompts and images<p>Except prompt-based tweaking doesn’t work very well in MJ; certainly not as well as manually-directed in-painting and out-painting. It’s virtually impossible in MJ to hold one part of the image constant while adding to/modifying the remainder.
Interesting, and I look forward to using it, but I wish the distribution had kept the folder-name conventions of AUTOMATIC1111, so that we could more easily have used symbolic links for folders of LoRAs and checkpoints etc. that we'd rather not duplicate.
definitely the smoothest install process and relatively snappy on my local windows machine that I've come across.
I do hope to see some ControlNet integrations as that's become a key part of my workflow for exploring new images.
Are there ways to run such apps with a remote GPU over network? I want to run the UI on my laptop, but use my homeserver GPU from the local network.<p>Anything better than X forwarding?
Just like I expected, I get this error when trying to run it on my AMD GPU...<p>"RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from <a href="http://www.nvidia.com/Download/index.aspx" rel="nofollow noreferrer">http://www.nvidia.com/Download/index.aspx</a>"<p>Maybe it can get modified to use DirectML? Although it looks like it's using PyTorch 2.0, and I think torch-directml only supports 1.13. Why is ML and GPGPU such a dependency mess?
Here's a live demo on HuggingFace <a href="https://huggingface.co/spaces/SpacesExamples/Fooocus" rel="nofollow noreferrer">https://huggingface.co/spaces/SpacesExamples/Fooocus</a>