taming-transformers
stable-diffusion-webui
Our great sponsors
taming-transformers | stable-diffusion-webui | |
---|---|---|
35 | 104 | |
5,354 | 5,487 | |
3.9% | - | |
0.0 | 10.0 | |
about 1 month ago | over 1 year ago | |
Jupyter Notebook | Python | |
MIT License | GNU Affero General Public License v3.0 |
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.
taming-transformers
-
Automatic1111 for Intel Arc (A380 Tested)
taming-transformers
-
[R] My simple Transformer audio encoder gives the same output for each timestep after the encoder
What’s your goal exactly? Are you trying to make a transformer based auto encoder of audio spectrograms? If so you should either start with either a proven ViT-based AE implementation (either a VAE or a VQ-GAN). But I don’t see why you necessarily need a ViT for this, if you’re working at a much smaller scale a convolutional architecture is plenty and much more amenable to beginners. See https://github.com/CompVis/taming-transformers for an example of a convolutional VQ GAN.
- Trying to make VqGAN+CLIP work again
-
im so lost
Command: "git" clone "https://github.com/CompVis/taming-transformers.git" "C:\AI\stable-diffusion-webui\repositories\taming-transformers"
-
Why is ChatGPT and other large language models not feasible to be used locally in consumer grade hardware while Stable Diffusion is?
See https://arxiv.org/abs/2012.09841 for prior work. SD authors swap out the Transformer and language modelling objective with a UNet diffusion objective. In general, the more inductive bias your model has, the more efficient it can be. ChatGPT runs purely on a Transformer architecture, which has far fewer priors than a CNN and requires far more parameters as a result. This may not be the case in the future.
-
1 or 2 Errors Installing Automatic1111 on Mac M1
There is definitely a cmd but I can't tell you. It's on GitHub https://github.com/CompVis/taming-transformers
-
Trying to Install InvokeAI and VectorQuantizer2 and taming modules but get error “zsh: parse error near `)’” How to fix? (MAC M1)
I wasn’t able to find a “taming” folder within the site-packages folder so I decided to look up how to get VectorQuantizer2 and taming.modules.vqvae.quantize and found this link: https://github.com/CompVis/taming-transformers/blob/master/taming/modules/vqvae/quantize.py I copied the raw contents and pasted that to the terminal and I got this error: “zsh: parse error near `)’” I’m not sure how to fix this so I can install VectorQuantizer2 so I can use InvokeAI. How do I fix this?
-
AI Is Coming For Commercial Art Jobs. Can It Be Stopped? (Greg Rutkowski quoted)
I say this to everyone... Even if SD and the model is legit and legal. Do not go around commercialising it's outputs or claiming ownership over them... and if you do the properly cite the source of the model and system along with it. In https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers and https://huggingface.co/CompVis/stable-diffusion-v1-4 there are citiations provided for you to use for a reason. I recommend you to use them.
-
Stable-diffusion in Nix
# Copy models as described in README cp ~/Downloads/model.ckpt . cp ~/Downloads/GFPGANv1.3.pth . # Clone other repos as mentioned in README mkdir repositories git clone https://github.com/CompVis/stable-diffusion.git repositories/stable-diffusion git clone https://github.com/CompVis/taming-transformers.git repositories/taming-transformers git clone https://github.com/sczhou/CodeFormer.git repositories/CodeFormer git clone https://github.com/salesforce/BLIP.git repositories/BLIP export NIXPKGS_ALLOW_UNFREE=1 nix-shell default.nix pip install torch --extra-index-url https://download.pytorch.org/whl/cu113 # Also from linux instructions. Can probably be added to default.nix python webui.py
-
[D] Where does VQ-GAN get its randomness from?
Code for https://arxiv.org/abs/2012.09841 found: https://compvis.github.io/taming-transformers/
stable-diffusion-webui
-
[Stable Diffusion] Je suis confus Aide? - Comment utilisez-vous LDSR avec SD-Webui?
[https://github.com/sd-webui/stable-diffusion-webui/wiki/installation de numéro(https://github.com/sd-webui/stable-diffusion-webui/wiki/installation)
-
[Stable Diffusion] Quelle est la meilleure interface graphique à installer sur Windows?
https://github.com/sd-webui/stable-diffusion-webui (prend beaucoup à installer)
- Daily General Discussion - October 21, 2022
-
Most popular IA to animate?
you can "animate" with stable diffusion usining text to video https://github.com/nateraw/stable-diffusion-videos or https://github.com/sd-webui/stable-diffusion-webui
-
Automatic1111 removed from pinned guide.
I mentioned Automatic1111 on SD-WEBUI and they deleted the comment. I guess this is why. My installation failed on SD-WEBUI and there was no solution for me. I suspect that's why Automatic1111's fork is so popular. He went above and beyond to make sure people with 1660ti's could run SD flawlessly with all the different tools available.
-
.pt to .ckpt
Any way to convert a .pt model to a .ckpt model? Stable-diffusion-webui only seems to support the second type of file but just renaming them does not work:
-
Flooded district by AI
This is Stable-Diffusion. Here is a UI version https://github.com/sd-webui/stable-diffusion-webui
-
AI image generated using the prompt "Streets of Dunwall"
I dunno about the app. I use this https://github.com/sd-webui/stable-diffusion-webui it's very resource hungry though.
-
NMKD Stable Diffusion GUI 1.5.0 is out! Now with exclusion words, CodeFormer face restoration, model merging and pruning tool, even lower VRAM requirements (4 GB), and a ton of quality-of-life improvements. Details in comments.
Haven't tried this GUI yet. Can anyone chime in about how it compares to Automatic1111's and sd-webui/HLKY's? There are so many good repos out there that it's getting hard to keep track of them all
-
Someone just joined 11 GPUs to the Stable Horde. I just tested: 20 gens @ 1024x1024x50 in 2 minutes! All for free!
Maybe those who joined were not aware that they joined the horde :-)
What are some alternatives?
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
diffusers-uncensored - Uncensored fork of diffusers
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
onnx - Open standard for machine learning interoperability
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]
rocm-build - build scripts for ROCm
stable-diffusion - A latent text-to-image diffusion model
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
waifu-diffusion - stable diffusion finetuned on weeb stuff