taming-transformers
CodeFormer
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taming-transformers | CodeFormer | |
---|---|---|
35 | 28 | |
5,354 | 13,396 | |
3.9% | - | |
0.0 | 2.0 | |
about 1 month ago | 29 days ago | |
Jupyter Notebook | Python | |
MIT License | 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.
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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
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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/
CodeFormer
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Automatic1111 for Intel Arc (A380 Tested)
CodeFormer
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Working with a prompt someone posted earlier ( workflow in comments)
https://github.com/sczhou/CodeFormer like this, did you install anything???
- Robust Blind Face Restoration with Codebook Lookup Transformer
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Images created in Automatic1111 on M1 Mac - Blue tint
https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth to /stable-diffusion-webui/models/Codeformer/codeformer-v0.1.0.pth
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How can I make this command run?
I just watched a youtube video of two minute papers and I was impressed by this face restauration ai.
- Towards Robust Blind Face Restoration with Codebook Lookup TransFormer | high quality faces!
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I tried restoring this REALY old photo of my wife's great great great great Grandpa.
Have you tried this instead? https://github.com/sczhou/CodeFormer , you can try it at https://replicate.com/sczhou/codeformer
- 12 best AI websites to make your life easier [save 100s of hours]
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Hoping to get this 1890's photo of my great grandmother and her 3 sisters restored as a Christmas present for my father.
CodeFormer is another good alternative to GFPGAN if you're not pleased with its results.
- new ai upscale tech
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]
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
GPEN
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]
Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
MidJourney-Styles-and-Keywords-Reference - A reference containing Styles and Keywords that you can use with MidJourney AI. There are also pages showing resolution comparison, image weights, and much more!
stable-diffusion - A latent text-to-image diffusion model
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]