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# Stable Diffusion web UI |
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A browser interface based on Gradio library for Stable Diffusion. |
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![](screenshot.png) |
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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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- [Segmind Stable Diffusion](https://huggingface.co/segmind/SSD-1B) support |
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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 gperftools-libs libglvnd-glx |
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# openSUSE-based: |
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sudo zypper install wget git python3 libtcmalloc4 libglvnd |
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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/Stability-AI/stablediffusion, 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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- Hypertile - tfernd - https://github.com/tfernd/HyperTile |
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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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