latent-diffusion
stable-diffusion
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latent-diffusion | stable-diffusion | |
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70 | 382 | |
10,512 | 65,243 | |
4.2% | 1.7% | |
0.0 | 0.0 | |
about 2 months ago | 5 days ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | GNU General Public License v3.0 or later |
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latent-diffusion
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SDXL: The next generation of Stable Diffusion models for text-to-image synthesis
Stable Diffusion XL (SDXL) is the latest text-to-image generation model developed by Stability AI, based on the latent diffusion techniques. SDXL has the potential to create highly realistic images for media, entertainment, education, and industry domains, opening new ways in practical uses of AI imagery.
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Is it possible to create a checkpoint from scratch?
Here's a link to the early latent-diffusion git, that might be able to create a blank model (I haven't tested it): https://github.com/CompVis/latent-diffusion
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Anything better than pix2pixHD?
Latent diffusion could work for you: https://github.com/CompVis/latent-diffusion (https://arxiv.org/abs/2112.10752)
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Image Upscaler AI
There are a lot but the one implemented as LDSR in most stable guis is this one. https://github.com/CompVis/latent-diffusion
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I've been collecting millions of images of only public domain /cc0 licensing. I'd like to train a stable diffusion model on the collection. Could some one share their knowledge of what this would take? Otherwise, simply enjoy my library.
CompVis/latent-diffusion: High-Resolution Image Synthesis with Latent Diffusion Models (github.com)
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Run Clip on iPhone to Search Photos
The "retrieval based model" refers to https://github.com/CompVis/latent-diffusion#retrieval-augmen..., which uses ScaNN to train a knn embedding searcher.
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Class Action Lawsuit filed against Stable Diffusion and Midjourney.
Stability is basically https://github.com/CompVis/latent-diffusion + training data.
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[D] Influential papers round-up 2022. What are your favorites?
Found relevant code at https://github.com/CompVis/latent-diffusion + all code implementations here
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Can anyone explain differences between sampling methods and their uses to me in simple terms, because all the info I've found so far is either very contradicting or complex and goes over my head
DDIM and PLMS were the original samplers. They were part of Latent Diffusion's repository. They stand for the papers that introduced them, Denoising Diffusion Implicit Models and Pseudo Numerical Methods for Diffusion Models on Manifolds.
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AI art is very dystopian.
yes, https://github.com/CompVis/latent-diffusion
stable-diffusion
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Go is bigger than crab!
Which is a 1-click install of Stable Diffusion with an alternative web interface. You can choose a different approach but this one is pretty simple and I am new to this stuff.
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Why & How to check Invisible Watermark
an invisible watermarking of the outputs, to help viewers identify the images as machine-generated.
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How to create an Image generating AI?
It sounds like you just want to set up Stable Diffusion to run locally. I don't think your computer's specs will be able to do it. You need a graphics card with a decent amount of VRAM. Stable diffusion is in Python as is almost every AI open source project I've seen. If you can get your hands on a system with an Nvidia RTX card with as much VRAM as possible, you're in business. I have an RTX 3060 with 12 gigs of VRAM and I can run stable diffusion and a whole variety of open source LLMs as well as other projects like face swap, Roop, tortoise TTS, sadtalker, etc...
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Two video cards...one dedicated to Stable Diffusion...the other for everything else on my PC?
Use specific GPU on multi GPU systems · Issue #87 · CompVis/stable-diffusion · GitHub
- Automatic1111 - Multiple GPUs
- Ist Google inzwischen einfach unbrauchbar?
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Why are people so against compensation for artists?
I dealt with this in one of my posts. At least SD 1.1 till 1.5 are all trained on a batch size of 2048. The version pretty much everyone uses (1.5) is first pretrained at a resolution of 256x256 for 237K steps on laion2B-en, at the end of those training steps it will have seen roughly 500M images in laion2B-en. After that it is pre-trained for 194K steps on laion-high-resolution at a resolution of 512x512, which is a subset of 170M images from laion5B. Finally it is trained for 1.110K steps on LAION aesthetic v2 5+. This is easily verified by taking a glance at the model card of SD 1.5. Though that one doesn't specify for part of the training exactly which aesthetic set was used for part of the training, for that you have to look at the CompVis github repo. Thus at the end of it all both the most recent images and the majority of images will have come from LAION aesthetic v2 5+ (seeing every image approx 4 times). Realistically a lot of the weights obtained from pretraining on 2B will have been lost, and only provided a good starting point for the weights.
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Is SDXL really open-source?
stable diffusion · CompVis/stable-diffusion@2ff270f · GitHub
- I want to ask the AI to draw me as a Pokemon anime character then draw six of Pokemon of my choice next to me. What are my best free, 15$ or under and 30$ or under choices?
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how can i create my own ai image model
Here for example --> https://github.com/CompVis/stable-diffusion
What are some alternatives?
disco-diffusion
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
dalle-mini - DALL·E Mini - Generate images from a text prompt
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
dalle-2-preview
diffusers-uncensored - Uncensored fork of diffusers
hent-AI - Automation of censor bar detection
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
stable-diffusion
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
onnx - Open standard for machine learning interoperability