diffusionbee-stable-diffusion-ui VS swift-diffusion

* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.

- https://diffusionbee.com/

- https://github.com/comfyanonymous/ComfyUI

- https://github.com/AUTOMATIC1111/stable-diffusion-webui

Interesting, will check it out to see how it compares with https://diffusionbee.com which I am using for last few months for fun.

It depends on what you are planning to do. Stable diffusion works great locally on both the dell+linux and the mac laptop I tried it on. This one was easy to use while exploring models from huggingface: https://diffusionbee.com/

diffusion bee is the easiest app to use.

If you have a Mac, I highly recommend DiffusionBee. It’s an app you can install on your computer and use as much as you want (even offline) for free. The website has older downloads but if you go here you can get the latest beta with more features: https://github.com/divamgupta/diffusionbee-stable-diffusion-ui/releases

Try these first: 1. https://drawthings.ai/ 2. https://diffusionbee.com/

Diffusion Bee

If you have a Mac, you can try this out too offline for free - https://diffusionbee.com (Go into the settings to make it the largest image size and you can also upscale it afterward - helpful for submitting larger artwork dimensions to distributors).

I am going to put model related code we use in a public repo soon (it is very similar to https://github.com/liuliu/swift-diffusion but in NHWC format). ANE will be around 25s if it runs. DT's default only uses GPUs and 35s is on GPU (yes, like you said, upscaling would take extra 10s).

The text encoder uses a new vocabulary set, make sure you copied them from open_clip repo: https://github.com/mlfoundations/open_clip (I have these also available at: https://github.com/liuliu/swift-diffusion/tree/liu/unet/examples/open_clip

Should be able too, if there is a need. I am more interested to support training hypernetwork from the app directly. The conversion script itself is open-source (https://github.com/liuliu/swift-diffusion/blob/main/examples/unet/main.swift), but not polished, and because Apple doesn't allow you to run Python on device, so I cannot make it as easy as typing a URL and get done. Need to figure out what the UX looks like without me providing a networked services ...

Hi, this is the first app in a while (probably 10 years) that I submitted to AppStore. I've done this app in 3 weeks, so there are a lot to be polished. The technology that enables this I discussed in depth in an accompanied blog post: https://liuliu.me/eyes/stretch-iphone-to-its-limit-a-2gib-mo...

Some parts of it (or major parts) is also available at https://github.com/liuliu/swift-diffusion. I plan to port more stuff back to swift-diffusion and make a CLI tool out of it (it is a bit more work than the app because I need to consider CUDA compatibility there).

AMA!