stable-diffusion
OnnxDiffusersUI
stable-diffusion | OnnxDiffusersUI | |
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26 | 1 | |
203 | 6 | |
- | - | |
0.0 | 10.0 | |
over 1 year ago | over 1 year ago | |
Jupyter Notebook | Python | |
GNU General Public License v3.0 or later | - |
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stable-diffusion
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Trying to merge model checkpoints and getting an error
Looks like Doggettx is a fork of CompVis/stable-diffusion, as a proof of concept:
- Stable Diffusion links from around September 11, 2022 that I collected for further processing
- Stable Diffusion for AMD GPUs on Windows using DirectML (Txt2Img, Img2Img & Inpainting) easy to setup (Python + Git)
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Has anyone made a commandline client to use Automatic1111's version of Stable Diffusion over the network?
Don't use a UI if you want terminal access. Use a project meant for terminal. https://github.com/Doggettx/stable-diffusion/tree/autocast-improvements
- Looking at cheap high VRAM old tesla cards to run stable diffusion at high res!
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Looking for a script I saw mentioned but can't find. Prompt Editing over Steps
The feature is just called prompt editing or prompt2prompt. It is also implemented in the Automatic1111 webui.
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Any way to fix this?
Depends on what fork you are using but its just means you are running out of vram since it states you only have 4gb of it. You may need to use the optimizedsd scripts and use the Doggettx's attention.py, you can find this in ldm/modules/attention.py (I personally have 2 of those in my own folder since I need to switch them but typically you require 6gb min for sd.
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Jabba The Hutt as a newborn
I installed SD from the CompVis GitHub repo and then swapped in modifications (namely attention.py and main.py) done by u/Doggettx that can be found here to overcome CUDA Out Of Memory issues. Going to try larger image sizes next. I wish you all good luck with concentrating on real work with this imaginatron around! ðŸ¤
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Stable Diffusion Gui Benchmark Results: Loading... Generated 1 image in 5.58s (20/20)
using optimized attention.py and model.py from this github issue.
- This community continues to blow me away. 8 days ago I was amazed by my 1408 x 960 resolution image. With all the new features I'm now doing 6 megapixel native output (3072x2048). That's 24 times more pixels than 512x512. Full workflow in comments.
OnnxDiffusersUI
What are some alternatives?
stable-diffusion
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
stable-diffusion-webui - Stable Diffusion web UI
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
dream-textures - Stable Diffusion built-in to Blender
stable-diffusion - A latent text-to-image diffusion model
stable-diffusion
text2image-gui - Somewhat modular text2image GUI, initially just for Stable Diffusion
Stable-textual-inversion_win
stable-diffusion-webui - Stable Diffusion web UI (neonsecret fork)