stablediffusion-directml
taming-transformers
stablediffusion-directml | taming-transformers | |
---|---|---|
6 | 35 | |
41 | 5,476 | |
- | 1.9% | |
3.6 | 0.0 | |
about 1 year ago | about 2 months ago | |
Python | Jupyter Notebook | |
MIT License | MIT License |
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stablediffusion-directml
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Automatic1111 for Intel Arc (A380 Tested)
stable-diffusion-stability-ai (Directml version)
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Stable Diffusion on AMD APUs
https://github.com/lshqqytiger/k-diffusion-directml/tree/master --->this will need to be named k-diffusion https://github.com/lshqqytiger/stablediffusion-directml/tree/main ----> this will need to be renamed stable-diffusion-stability-ai
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What am I doing wrong? Inpainting reverts to original...
I'm using the directml fork of the Automatic1111 web gui on my AMD RX 6800 XT , and it seems to work fine with txt2img, but my attempts at inpainting to fix up the faces is getting me nowhere. This isn't the browser issue, in that the faces are being shown as being edited in the preview, but they successively converge on the original bad image that's masked... I've attached a youtube clip of how it goes for me. Help!
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Man I wish I could do all this cool shit too
Download k-diffusion and stablediffusion folders. (click green button "Code" and download as ZIP). Go to the folder you installed in step 1 and browse to repositories, extract these two folders there. Rename them to k-diffusion and stable-diffusion-stability-ai. If you already have these folders delete them first.
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SD made me regret buying an AMD card.
There is couple options, easy one for windows is this fork https://github.com/lshqqytiger/stablediffusion-directml you don't need to convert models to onyxxx is simply a1111 using directml so you can use all features like controlnet, but will be probably slower than shark or linux a1111 with rocm (why the hell is there no rocm for windows :/), tbh If I were you, I'd probably try to sell the card and buy, for example, a 3060 12GB
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Intel Arc Stable difussion?
3) install k-diffusion-directml and stablediffusion-directm under ..\stable-diffusion-webui-arc-directml-master\repositories (tutorial)
taming-transformers
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Automatic1111 for Intel Arc (A380 Tested)
taming-transformers
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[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
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im so lost
Command: "git" clone "https://github.com/CompVis/taming-transformers.git" "C:\AI\stable-diffusion-webui\repositories\taming-transformers"
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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.
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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
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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?
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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.
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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
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[D] Where does VQ-GAN get its randomness from?
Code for https://arxiv.org/abs/2012.09841 found: https://compvis.github.io/taming-transformers/
What are some alternatives?
SHARK - SHARK - High Performance Machine Learning Distribution
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]
stable-diffusion-webui-colab - stable diffusion webui colab
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
CodeFormer - [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
civitai - A repository of models, textual inversions, and more
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]
stable-diffusion-webui-arc-directml - A proven usable Stable diffusion webui project on Intel Arc GPU with DirectML
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
stable-diffusion-webui-amdgpu - Stable Diffusion web UI
stable-diffusion - A latent text-to-image diffusion model