Graphite VS automatic

There is also Graphite (https://graphite.rs/) which, unlike Gimp, has a modern architecture and very ambitious goals (Blender for 2D basically).

If you're interested in either computational geometry, layout/packing/constraints, or functional programming language concepts, those are all the math-related concepts that we're currently interacting with for Graphite, a 2D vector graphics editor that's aiming to become the next Blender (but for 2D instead of 3D). If that sounds interesting, I'd love to help get you started if you want to join our Discord and I can explain the math-related work that we need to get done. Cheers!

Not sure which web-based spreadsheet app you're talking about, because there are many that do use these frameworks. Here's a PS/AI clone built with a Svelte frontend: https://graphite.rs

Wanted to contribute to a good Rust-based project last week, started searching and found a good Reddit thread featuring several great projects. Looked at and found Graphite. I liked the concept though I know almost nothing about graphic design.

I'm currently trying to decide on the SD server to deploy with Graphite, both for running locally (with Tauri desktop builds) and for us to host on a server for users.

> it won't ever be a viable option

For production workloads, I generally agree. It's an unsupported hack with a questionable future, I wouldn't do anything money-making with it.

However, for tinkering and consumer workloads, it already works pretty well. Enough of cuDNN and cuBLAS work to run PyTorch and in turn, Stable Diffusion with https://github.com/lshqqytiger/ZLUDA - there's even a fairly user-friendly setup process already in https://github.com/vladmandic/automatic .

I was able to get a personal non-ML related project working on my AMD card in just a few minutes, which saved me a lot of development time before I then deployed the production workload on NV hardware (this is probably why AMD pulled the plug on the project - it's almost more of a boost to NV than anything else, AMD really need people to be writing code on ROCm to deploy on AMD datacenter hardware).

While I currently use SD.Next[1], I have tested ComfyUI locally with my AMD card. The UI can be daunting, but you learn quite a great deal about how a Stable Diffusion pipeline works. In addition some innovations and advances find their way into ComfyUI first.

[1] https://github.com/vladmandic/automatic

I used SD.NEXT ( https://github.com/vladmandic/automatic ) and https://civitai.com/models/82098/add-more-details-detail-enhancer-tweaker-lora and epicphotogasm_lastUnicorn

I found this thread on GitHub talking about how this was fixed in the latest version with an optional setting. I tried enabling it, as they mentioned, but it just resulted in an immediate CUDA out of memory error when starting generation. So it seems I'm actually needing the shared memory, which I assume is my issue.

As always, do check out our more detailed changelog, give us a quick install from our Repo, and stop by our Discord Server for any questions or help you may need.

SD.Next

Today I finally wanted to give SDXL a chance, so I set everythin up according to Vladmandic's Wiki https://github.com/vladmandic/automatic/wiki/SD-XL

I'm trying to get SDXL working on Vlad's SDNext, but I keep getting the error in the title when trying to run basic operations. I'm not sure what's going on, I followed his guide for it to a T.

We used an inference container based on SDNext, along with a custom worker written in Typescript that implemented the job processing pipeline. The worker used HTTP to communicate with both the SDNext container and with our batch framework.