178 lines
12 KiB
Markdown
178 lines
12 KiB
Markdown
# Stable Diffusion web UI
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A browser interface based on Gradio library for Stable Diffusion.
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## Features
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[Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features):
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- Original txt2img and img2img modes
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- One click install and run script (but you still must install python and git)
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- Outpainting
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- Inpainting
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- Color Sketch
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- Prompt Matrix
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- Stable Diffusion Upscale
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- Attention, specify parts of text that the model should pay more attention to
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- a man in a `((tuxedo))` - will pay more attention to tuxedo
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- a man in a `(tuxedo:1.21)` - alternative syntax
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- select text and press `Ctrl+Up` or `Ctrl+Down` (or `Command+Up` or `Command+Down` if you're on a MacOS) to automatically adjust attention to selected text (code contributed by anonymous user)
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- Loopback, run img2img processing multiple times
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- X/Y/Z plot, a way to draw a 3 dimensional plot of images with different parameters
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- Textual Inversion
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- have as many embeddings as you want and use any names you like for them
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- use multiple embeddings with different numbers of vectors per token
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- works with half precision floating point numbers
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- train embeddings on 8GB (also reports of 6GB working)
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- Extras tab with:
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- GFPGAN, neural network that fixes faces
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- CodeFormer, face restoration tool as an alternative to GFPGAN
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- RealESRGAN, neural network upscaler
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- ESRGAN, neural network upscaler with a lot of third party models
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- SwinIR and Swin2SR ([see here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/2092)), neural network upscalers
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- LDSR, Latent diffusion super resolution upscaling
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- Resizing aspect ratio options
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- Sampling method selection
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- Adjust sampler eta values (noise multiplier)
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- More advanced noise setting options
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- Interrupt processing at any time
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- 4GB video card support (also reports of 2GB working)
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- Correct seeds for batches
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- Live prompt token length validation
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- Generation parameters
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- parameters you used to generate images are saved with that image
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- in PNG chunks for PNG, in EXIF for JPEG
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- can drag the image to PNG info tab to restore generation parameters and automatically copy them into UI
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- can be disabled in settings
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- drag and drop an image/text-parameters to promptbox
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- Read Generation Parameters Button, loads parameters in promptbox to UI
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- Settings page
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- Running arbitrary python code from UI (must run with `--allow-code` to enable)
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- Mouseover hints for most UI elements
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- Possible to change defaults/mix/max/step values for UI elements via text config
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- Tiling support, a checkbox to create images that can be tiled like textures
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- Progress bar and live image generation preview
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- Can use a separate neural network to produce previews with almost none VRAM or compute requirement
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- Negative prompt, an extra text field that allows you to list what you don't want to see in generated image
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- Styles, a way to save part of prompt and easily apply them via dropdown later
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- Variations, a way to generate same image but with tiny differences
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- Seed resizing, a way to generate same image but at slightly different resolution
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- CLIP interrogator, a button that tries to guess prompt from an image
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- Prompt Editing, a way to change prompt mid-generation, say to start making a watermelon and switch to anime girl midway
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- Batch Processing, process a group of files using img2img
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- Img2img Alternative, reverse Euler method of cross attention control
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- Highres Fix, a convenience option to produce high resolution pictures in one click without usual distortions
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- Reloading checkpoints on the fly
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- Checkpoint Merger, a tab that allows you to merge up to 3 checkpoints into one
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- [Custom scripts](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Custom-Scripts) with many extensions from community
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- [Composable-Diffusion](https://energy-based-model.github.io/Compositional-Visual-Generation-with-Composable-Diffusion-Models/), a way to use multiple prompts at once
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- separate prompts using uppercase `AND`
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- also supports weights for prompts: `a cat :1.2 AND a dog AND a penguin :2.2`
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- No token limit for prompts (original stable diffusion lets you use up to 75 tokens)
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- DeepDanbooru integration, creates danbooru style tags for anime prompts
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- [xformers](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Xformers), major speed increase for select cards: (add `--xformers` to commandline args)
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- via extension: [History tab](https://github.com/yfszzx/stable-diffusion-webui-images-browser): view, direct and delete images conveniently within the UI
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- Generate forever option
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- Training tab
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- hypernetworks and embeddings options
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- Preprocessing images: cropping, mirroring, autotagging using BLIP or deepdanbooru (for anime)
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- Clip skip
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- Hypernetworks
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- Loras (same as Hypernetworks but more pretty)
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- A separate UI where you can choose, with preview, which embeddings, hypernetworks or Loras to add to your prompt
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- Can select to load a different VAE from settings screen
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- Estimated completion time in progress bar
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- API
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- Support for dedicated [inpainting model](https://github.com/runwayml/stable-diffusion#inpainting-with-stable-diffusion) by RunwayML
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- via extension: [Aesthetic Gradients](https://github.com/AUTOMATIC1111/stable-diffusion-webui-aesthetic-gradients), a way to generate images with a specific aesthetic by using clip images embeds (implementation of [https://github.com/vicgalle/stable-diffusion-aesthetic-gradients](https://github.com/vicgalle/stable-diffusion-aesthetic-gradients))
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- [Stable Diffusion 2.0](https://github.com/Stability-AI/stablediffusion) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#stable-diffusion-20) for instructions
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- [Alt-Diffusion](https://arxiv.org/abs/2211.06679) support - see [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#alt-diffusion) for instructions
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- Now without any bad letters!
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- Load checkpoints in safetensors format
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- Eased resolution restriction: generated image's dimensions must be a multiple of 8 rather than 64
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- Now with a license!
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- Reorder elements in the UI from settings screen
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## Installation and Running
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Make sure the required [dependencies](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Dependencies) are met and follow the instructions available for:
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- [NVidia](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs) (recommended)
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- [AMD](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs) GPUs.
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- [Intel CPUs, Intel GPUs (both integrated and discrete)](https://github.com/openvinotoolkit/stable-diffusion-webui/wiki/Installation-on-Intel-Silicon) (external wiki page)
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Alternatively, use online services (like Google Colab):
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- [List of Online Services](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Online-Services)
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### Installation on Windows 10/11 with NVidia-GPUs using release package
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1. Download `sd.webui.zip` from [v1.0.0-pre](https://github.com/AUTOMATIC1111/stable-diffusion-webui/releases/tag/v1.0.0-pre) and extract its contents.
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2. Run `update.bat`.
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3. Run `run.bat`.
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> For more details see [Install-and-Run-on-NVidia-GPUs](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-NVidia-GPUs)
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### Automatic Installation on Windows
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1. Install [Python 3.10.6](https://www.python.org/downloads/release/python-3106/) (Newer version of Python does not support torch), checking "Add Python to PATH".
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2. Install [git](https://git-scm.com/download/win).
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3. Download the stable-diffusion-webui repository, for example by running `git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git`.
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4. Run `webui-user.bat` from Windows Explorer as normal, non-administrator, user.
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### Automatic Installation on Linux
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1. Install the dependencies:
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```bash
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# Debian-based:
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sudo apt install wget git python3 python3-venv libgl1 libglib2.0-0
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# Red Hat-based:
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sudo dnf install wget git python3
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# Arch-based:
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sudo pacman -S wget git python3
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```
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2. Navigate to the directory you would like the webui to be installed and execute the following command:
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```bash
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wget -q https://raw.githubusercontent.com/AUTOMATIC1111/stable-diffusion-webui/master/webui.sh
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```
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3. Run `webui.sh`.
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4. Check `webui-user.sh` for options.
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### Installation on Apple Silicon
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Find the instructions [here](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Installation-on-Apple-Silicon).
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## Contributing
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Here's how to add code to this repo: [Contributing](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Contributing)
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## Documentation
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The documentation was moved from this README over to the project's [wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki).
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For the purposes of getting Google and other search engines to crawl the wiki, here's a link to the (not for humans) [crawlable wiki](https://github-wiki-see.page/m/AUTOMATIC1111/stable-diffusion-webui/wiki).
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## Credits
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Licenses for borrowed code can be found in `Settings -> Licenses` screen, and also in `html/licenses.html` file.
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- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
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- k-diffusion - https://github.com/crowsonkb/k-diffusion.git
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- GFPGAN - https://github.com/TencentARC/GFPGAN.git
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- CodeFormer - https://github.com/sczhou/CodeFormer
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- ESRGAN - https://github.com/xinntao/ESRGAN
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- SwinIR - https://github.com/JingyunLiang/SwinIR
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- Swin2SR - https://github.com/mv-lab/swin2sr
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- LDSR - https://github.com/Hafiidz/latent-diffusion
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- MiDaS - https://github.com/isl-org/MiDaS
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- Ideas for optimizations - https://github.com/basujindal/stable-diffusion
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- Cross Attention layer optimization - Doggettx - https://github.com/Doggettx/stable-diffusion, original idea for prompt editing.
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- Cross Attention layer optimization - InvokeAI, lstein - https://github.com/invoke-ai/InvokeAI (originally http://github.com/lstein/stable-diffusion)
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- Sub-quadratic Cross Attention layer optimization - Alex Birch (https://github.com/Birch-san/diffusers/pull/1), Amin Rezaei (https://github.com/AminRezaei0x443/memory-efficient-attention)
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- Textual Inversion - Rinon Gal - https://github.com/rinongal/textual_inversion (we're not using his code, but we are using his ideas).
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- Idea for SD upscale - https://github.com/jquesnelle/txt2imghd
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- Noise generation for outpainting mk2 - https://github.com/parlance-zz/g-diffuser-bot
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- CLIP interrogator idea and borrowing some code - https://github.com/pharmapsychotic/clip-interrogator
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- Idea for Composable Diffusion - https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch
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- xformers - https://github.com/facebookresearch/xformers
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- DeepDanbooru - interrogator for anime diffusers https://github.com/KichangKim/DeepDanbooru
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- Sampling in float32 precision from a float16 UNet - marunine for the idea, Birch-san for the example Diffusers implementation (https://github.com/Birch-san/diffusers-play/tree/92feee6)
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- Instruct pix2pix - Tim Brooks (star), Aleksander Holynski (star), Alexei A. Efros (no star) - https://github.com/timothybrooks/instruct-pix2pix
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- Security advice - RyotaK
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- UniPC sampler - Wenliang Zhao - https://github.com/wl-zhao/UniPC
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- TAESD - Ollin Boer Bohan - https://github.com/madebyollin/taesd
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- LyCORIS - KohakuBlueleaf
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- Restart sampling - lambertae - https://github.com/Newbeeer/diffusion_restart_sampling
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- Initial Gradio script - posted on 4chan by an Anonymous user. Thank you Anonymous user.
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- (You)
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