ROCm-docker
InvokeAI
ROCm-docker | InvokeAI | |
---|---|---|
3 | 239 | |
392 | 21,337 | |
1.0% | 1.4% | |
5.1 | 10.0 | |
24 days ago | 5 days ago | |
Shell | TypeScript | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ROCm-docker
-
AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
https://rocm.docs.amd.com/projects/install-on-linux/en/lates... links to ROCm/ROCm-docker: https://github.com/ROCm/ROCm-docker which is the source of docker.io/rocm/rocm-terminal: https://hub.docker.com/r/rocm/rocm-terminal :
docker run -it --device=/dev/kfd --device=/dev/dri --group-add video rocm/rocm-terminal
-
Stable Diffusion PR optimizes VRAM, generate 576x1280 images with 6 GB VRAM
Not sure about the 6600, but there is a guide for Linux at least:
https://m.youtube.com/watch?v=d_CgaHyA_n4&feature=emb_logo
And this is somehow relevant (possibly), as I kept the link open.
https://github.com/RadeonOpenCompute/ROCm-docker/issues/38
-
It's working perfectly under Linux
As for the Docker image, I suppose you could compile the image (https://hub.docker.com/r/rocm/pytorch) by yourself using the sources (https://github.com/RadeonOpenCompute/ROCm-docker#building-images), which seems to be quite a bit of work. Better, you could just use an older tag of the upstream image, eg. rocm4.1.1_ubuntu18.04_py3.6_pytorch instead of rocm4.2_ubuntu18.04_py3.6_caffe2 or latest . Just make sure your container version matches your host ROCm version.
InvokeAI
-
Stable Diffusion 3
Probably not, since I have no idea what you're talking about. I've just been using the models that InvokeAI (2.3, I only just now saw there's a 3.0) downloads for me [0]. The SD1.5 one is as good as ever, but the SD2 model introduces artifacts on (many, but not all) faces and copyrighted characters.
[0] https://github.com/invoke-ai/InvokeAI
-
AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
I actually used the rocm/pytorch image you also linked.
I'm not sure what you're pointing to with your reference to the Fedora-based images. I'm quite happy with my NixOS install and really don't want to switch to anything else. And as long as I have the correct kernel module, my host OS really shouldn't matter to run any of the images.
And I'm sure it can be made to work with many base images, my point was just that the dependency management around pytorch was in a bad state, where it is extremely easy to break.
> Anyways, hopefully this PR fixes the immediate issue: https://github.com/invoke-ai/InvokeAI/pull/5714/files
It does! At least for me. It is my PR after all ;)
-
Can some expert analyze a github repo and tell us if it's really safe or not?
The data being flagged is not in that github repo, it's fetched from elsewhere and I don't fancy spending time looking for it. The alert is for 'Sirefef!cfg' which has been reported as a false positive with a bunch of other stable diffusion projects (https://www.reddit.com/r/StableDiffusion/comments/101zjec/trojanwin32sirefefcfg_an_apparently_common_false/, https://www.reddit.com/r/StableDiffusion/comments/xmhukb/trojan_in_waifudiffusion_model_file/, https://github.com/invoke-ai/InvokeAI/issues/2773 )
-
What is the most effcient port of SD to mac?
I haven’t tried it recently, but InvokeAI runs on Mac. Invoke. I used to run on my MacBook, but have since gotten a Win laptop.
-
Easy Stable Diffusion XL in your device, offline
There are already a number of local, inference options that are (crucially) open-source, with more robust feature sets.
And if the defense here is "but Auto1111 and Comfy don't have as user-friendly a UI", that's also already covered. https://github.com/invoke-ai/InvokeAI
-
Ask HN: Selfhosted ChatGPT and Stable-diffusion like alternatives?
https://github.com/invoke-ai/InvokeAI should work on your machine. For LLM models, the smaller ones should run using llama.cpp, but I don't think you'll be happy comparing them to ChatGPT.
- 🚀 InvokeAI 3.4 now supports LCM & LCM-LoRAs and much more!
-
Best ai image generator without a nsfw filter?
Stable Diffusion. /r/stablediffusion There are many tutorials on how to set it up locally and use it. InvokeAI is the easiest way to set it up. https://github.com/invoke-ai/InvokeAI
-
What's the best stable diffusion client for base m1 MacBook air?
InvokeAI
- invoke-ai/InvokeAI
What are some alternatives?
awesome-kubernetes - A curated list for awesome kubernetes sources :ship::tada:
stable-diffusion-webui - Stable Diffusion web UI
AiDungeon2-Docker-ROCm - Runs an AIDungeon2 fork in Docker on AMD ROCm hardware.
stable-diffusion
ZLUDA - CUDA on AMD GPUs
ControlNet - Let us control diffusion models!
stable-diffusion - Go to lstein/stable-diffusion for all the best stuff and a stable release. This repository is my testing ground and it's very likely that I've done something that will break it.
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
docker-elk - The Elastic stack (ELK) powered by Docker and Compose.
dreambooth-gui
Dokku - A docker-powered PaaS that helps you build and manage the lifecycle of applications
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM