disco-diffusion
By alembics
CLIP-Guided-Diffusion
Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. (by nerdyrodent)
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| disco-diffusion | CLIP-Guided-Diffusion | |
|---|---|---|
| 22 | 4 | |
| 7,454 | 377 | |
| 0.2% | - | |
| 0.0 | 0.0 | |
| 10 months ago | over 1 year ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
disco-diffusion
Posts with mentions or reviews of disco-diffusion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-23.
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Halloween 2022
Disco-diffusion, a framework like Stable, which came out about 13 months ago: https://github.com/alembics/disco-diffusion
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Which is your favorite text to image model overall?
Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.
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AI Generated Music Video using Disco Diffusion software
From the Disco Diffusion GitHub, "“A frankensteinian amalgamation of notebooks, models and techniques for the generation of AI Art and Animations.”
- List of open source machine learning AI image generation/text-to-image libraries that can be installed on an Amazon GPU instance? e.g. MinDall-E, Disco Diffusion, Pixray
- Colab notebook "Disco Diffusion v5.6, Inpainting_mode by cut_pow" by kostarion. From the developer: "Inpainting mode in #DiscoDiffusion! I've finally made the parametrised guided inpainting for disco, and applied it for more stable 2D and 3D animations. In the thread i show what's in there".
- I used an AI to create EVE Online themed Art!
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A good tutorial to get started?
Google Colab is probably the easiest way to run DD. To find the most recent version go to the GitHub page and then open the link to the Colab. Initially, you'll probably just want to experiment with the prompts. But there's also Zippy's Disco Diffusion Cheatsheet v0.3 which can be a useful place to learn more.
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Free/open-source AI Text-To-Image Models that can be run on AWS?
You can probably port Disco Diffusion pretty easily. It’s available on Google Colab, so should be straightforward. Their GitHub is: https://github.com/alembics/disco-diffusion
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Protests erupt outside of DALL-E offices after pricing implementation, press photograph
https://www.reddit.com/r/DiscoDiffusion/, https://github.com/alembics/disco-diffusion. As far as I'm aware the only way to use this is via Google Colab. Rather difficult to use because of this.
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First nice portrait on 5.6 running locally on 2070 (comparison untouched / GFPGAN)
https://github.com/alembics/disco-diffusion,
CLIP-Guided-Diffusion
Posts with mentions or reviews of CLIP-Guided-Diffusion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-23.
-
Which is your favorite text to image model overall?
Runner-ups are Craiyon (for being more "creative" than SD), Disco Diffusion, minDALL-E, and CLIP Guided Diffusion.
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Once have access, do you run it on your computer or over the internet on Open-AI's computers?
-clip guided diffusion https://github.com/nerdyrodent/CLIP-Guided-Diffusion
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how would i go about running disco diffusion locally?
Nerdy Rodent has a Github repo for this; it should work fine from the Anaconda command line: https://github.com/nerdyrodent/CLIP-Guided-Diffusion
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PLAYING AGAIN (CLIP GUIDED DIFFUSION) (VQGAN + CLIP) (Beksinski)
As far as I understand, VQGAN is not a guided diffusion model. I've been using a slightly tweaked version of https://github.com/nerdyrodent/CLIP-Guided-Diffusion for diffusion. Once you get it set up the interface is pretty much what you might expect:
What are some alternatives?
When comparing disco-diffusion and CLIP-Guided-Diffusion you can also consider the following projects:
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
DALLE-mtf - Open-AI's DALL-E for large scale training in mesh-tensorflow.
dalle-2-preview
big-sleep - A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN. Technique was originally created by https://twitter.com/advadnoun
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
vqgan-clip-app - Local image generation using VQGAN-CLIP or CLIP guided diffusion
feed_forward_vqgan_clip - Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
mindall-e - PyTorch implementation of a 1.3B text-to-image generation model trained on 14 million image-text pairs
disco-diffusion vs latent-diffusion
CLIP-Guided-Diffusion vs VQGAN-CLIP
disco-diffusion vs DALLE2-pytorch
CLIP-Guided-Diffusion vs DALLE-mtf
disco-diffusion vs dalle-2-preview
CLIP-Guided-Diffusion vs big-sleep
disco-diffusion vs CLIP
CLIP-Guided-Diffusion vs vqgan-clip-app
disco-diffusion vs big-sleep
CLIP-Guided-Diffusion vs feed_forward_vqgan_clip
disco-diffusion vs VQGAN-CLIP
CLIP-Guided-Diffusion vs mindall-e