guided-diffusion
disco-diffusion
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guided-diffusion | disco-diffusion | |
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14 | 22 | |
5,439 | 7,454 | |
4.8% | 0.5% | |
0.0 | 0.0 | |
12 months ago | 9 months ago | |
Python | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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guided-diffusion
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Why is there speculation that midjourney is based on stable diffusion if MJ is released earlier than SD?
People who made these colabs better and better also the same people who are at Midjourney now. But the "mother" of it all, was Katherine Crowson. She made a fine tuned model that uses a 512x512 unconditional ImageNet diffusion model fine-tuned from OpenAI's 512x512 class-conditional ImageNet diffusion model (https://github.com/openai/guided-diffusion) together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images. It uses a smaller secondary diffusion model trained by Katherine Crowson to remove noise from intermediate timesteps to prepare them for CLIP.
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We just release a complete open-source solution for accelerating Stable Diffusion pretraining and fine-tuning!
Our codebase for the diffusion models builds heavily on OpenAI's ADM codebase , lucidrains, Stable Diffusion, Lightning and Hugging Face. Thanks for open-sourcing!
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New custom inpainting model
this code is (mostly) just the original openai guided diffusion code: https://github.com/openai/guided-diffusion
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What was Disco trained with?
Original notebook by Katherine Crowson (https://github.com/crowsonkb, https://twitter.com/RiversHaveWings). It uses either OpenAI's 256x256 unconditional ImageNet or Katherine Crowson's fine-tuned 512x512 diffusion model (https://github.com/openai/guided-diffusion), together with CLIP (https://github.com/openai/CLIP) to connect text prompts with images.
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[D] Diffusion Models Beat GANs on Image Synthesis Explained: 5-minute paper summary (by Casual GAN Papers)
arxiv / code
Code for https://arxiv.org/abs/2105.05233 found: https://github.com/openai/guided-diffusion
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Diffusion Models Beat GANs on Image Synthesis
Although the weights aren't available, I wanted to note that the model source itself is actually available at https://github.com/openai/guided-diffusion.
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.
- 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
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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,
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What was Disco trained with?
From the Disco Diffusion GitHub repo:
- Once have access, do you run it on your computer or over the internet on Open-AI's computers?
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Up and running on VAST.AI!!
Now download this https://github.com/alembics/disco-diffusion/blob/main/Disco_Diffusion.ipynb and upload it in "Files"
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DALL-E 2 open source implementation
Also very interested in this. AFAIK, the best alternative to DALLE-type generation is CLIP-Guided generation (such as Disco Diffusion [1] and MidJourney[2]) which can take anywhere from 1 - 20 minutes on an RTX A5000.
What are some alternatives?
latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models
DALLE2-pytorch - Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
dalle-2-preview
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
artroom-stable-diffusion
CLIP-Guided-Diffusion - Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.
discoart - 🪩 Create Disco Diffusion artworks in one line
dalle-mini - DALL·E Mini - Generate images from a text prompt
disco-diffusion-1
score_sde - Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)