rocm-gfx803
stable-diffusion
rocm-gfx803 | stable-diffusion | |
---|---|---|
7 | 142 | |
167 | 2,438 | |
- | - | |
1.1 | 9.8 | |
about 1 year ago | over 1 year ago | |
Jupyter Notebook | ||
- | GNU General Public License v3.0 or later |
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-gfx803
- ROCm gfx803 archlinux
-
My brother is giving away a PC he built with 8 AMD Radeon RX Vega x64 GPUs (8GB ram). I've only ever done ML on Nvidia cards. Is there anything I can do with these?
That specific card has current support for rocm and that is supported by at least tensorflow and torch, plus many other less known/used libraries like cupy, although you are correct in the fact that support sucks in the long run, I have a GPU that is known to be useful and that has continued COMMUNITY support because AMD cut the support with rocm 4.0, thanks to Xuhuisheng for the patch to make the rx580 work with current rocm despite AMD lack of support, what open source can accomplish https://github.com/xuhuisheng/rocm-gfx803
-
Automatic111 - Torch is not able to use GPU. Help!
You'll also need to compile pytorch and torchvision for gfx803, although I recommend you install the whl files from here inside your venv because it's a massive pain to compile them on non-Ubuntu (I tried)
-
Image Creation Time for each GPU.
I followed the guide from here: https://github.com/xuhuisheng/rocm-gfx803
-
I *think* it's impossible to run SD on an RX 570 (and probably below?)
There is an unofficial build of ROCm 5.2.0 + pytorch + torchvision with GFX8 support added back in. I have no idea if it works. Perhaps someone who knows Docker/Conda could get SD working with those files.
- Run Stable Diffusion on Intel CPUs
stable-diffusion
- [Stable Diffusion] Aide nécessaire à l'augmentation de la taille du fichier maximum sur l'installation locale
- [Machine Learning] [P] Exécutez une diffusion stable sur le GPU de votre M1 Mac
- Its time!
-
Anybody running SD on a Macbook Pro? What are you using and how did you install it?
Yes, you can install it with Python! https://github.com/lstein/stable-diffusion works with macOS, and you can control all the common parameter via their WebUI or CLI :)
-
How do I save the arguments for images I create when using the terminal? (Apple M1 Pro)
I'm using lstein fork ("dream") and when I create an image from the terminal, it also writes back to the terminal like this:
- I Resurrected “Ugly Sonic” with Stable Diffusion Textual Inversion
-
AI Seamless Texture Generator Built-In to Blender
> Whenever I ask for something like ‘seamless tiling xxxxxx’ it kinda sorta gets the idea, but the resulting texture doesn’t quite tile right.
Getting seamless tiling requires more than just have "seamless tiling" in the prompt. It also depends on if the fork you're using has that feature at all.
https://github.com/lstein/stable-diffusion has the feature, but you need to pass it outside the prompt. So if you use the `dream.py` prompt cli, you can pass it `"Hats on the ground" --seamless` and it should be perfectly tilable.
-
Auto SD Workflow - Update 0.2.0 - "Collections", Password Protection, Brand new UI + more
From https://github.com/lstein/stable-diffusion
-
Stable Diffusion GUIs for Apple Silicon
Stable Diffusion Dream Script: This is the original site/script for supporting macOS. I found this soon after Stable Diffusion was publicly released and it was the site which inspired me to try out using Stable Diffusion on a mac. They have a web-based UI (as well as command-line scripts) and a lot of documentation on how to get things working.
-
Still can't believe this technology is real. My talentless 2 minute sketch on the left.
I’m pretty sure it works for M2 as well - basically the newer ARM-based Macs. The instructions to get it working are detailed! https://github.com/lstein/stable-diffusion
What are some alternatives?
stable-diffusion-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
waifu-diffusion - stable diffusion finetuned on weeb stuff
AITemplate - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
taming-transformers - Taming Transformers for High-Resolution Image Synthesis
stable-diffusion-cpu
stable-diffusion-webui - Stable Diffusion web UI
openvino - OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
diffusers-uncensored - Uncensored fork of diffusers
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.
txt2imghd - A port of GOBIG for Stable Diffusion
DeepSpeed-MII - MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.
dream-textures - Stable Diffusion built-in to Blender