* **[CompVis/Stable Diffusion](https://github.com/CompVis/stable-diffusion)** - The official release of Stable Diffusion including a CLI, an AI-based Safety Classifier, which detects and suppresses sexualized content, and all the necessary files to get running.
* [stability-AI/stability-sdk](https://github.com/stability-AI/stability-sdk) - The official SDK used to build python applications integrated with StabilityAI's cloud platform instead of hosting the model locally. Operation requires an API Key (🖊️💵).
* [Public Release Announcement](https://stability.ai/blog/stable-diffusion-public-release) - StabilityAI's announcement about the public release of Stable Diffusion.
* [laion-aesthetic](https://laion-aesthetic.datasette.io/laion-aesthetic-6pls/images) - The dataset used train stable diffusion, useful for querying to see if a concept is represented.
All forks listed here add additional features and optimisations and are generally faster than the original release, as they keep the model in memory rather than reloading it after every prompt. Most forks seem to remove the Safety Classifier which may present a risk if used to provide public-facing services, such as Discord bots.
* [AbdBarho/stable-diffusion-webui-docker](https://github.com/AbdBarho/stable-diffusion-webui-docker) - Easy Docker setup for SD with multiple user-friendly UI options including [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui), [sd-webui/stable-diffusion-webui](https://github.com/sd-webui/stable-diffusion-webui) and [invoke-ai/InvokeAI](https://github.com/invoke-ai/InvokeAI).
* [basujindal/stable-diffusion](https://github.com/basujindal/stable-diffusion) - "Optimized Stable Diffusion"—a fork with dramatically reduced VRAM requirements through model splitting, enabling Stable Diffusion on lower-end graphics cards; includes a GradIO web interface and support for weighted prompts.
* [bes-dev/stable_diffusion.openvino](https://github.com/bes-dev/stable_diffusion.openvino) - A fork for running the model using a CPU compatible with OpenVINO.
* [imaginAIry](https://github.com/brycedrennan/imaginAIry) - Pythonic generation of stable diffusion images. Unique in that it supports complex text-based masking. Has an interactive CLI, upscaling, face enhancement, tiling, and other standard features. No GUI.
* [invoke-ai/InvokeAI](https://github.com/invoke-ai/InvokeAI) - (formerly known as lstein/stable-diffusion) - Very active fork adding a conversational CLI, basic web interface and support for GFPGAN, ESRGAN, Codeformer, weighted prompts, prompt blending, negative prompting, img2img, tiling, [textual-inversion](https://textual-inversion.github.io/) as well as inference on Apple M1.
* [KerasCV StableDiffusion](https://keras.io/guides/keras_cv/generate_images_with_stable_diffusion/) - High performance implementation of stable diffusion on KerasCV.
* [lowfuel/progrock-stable](https://github.com/lowfuel/progrock-stable) - Fork with optional Web GUI and a different approach to upscaling (GoBIG/ESRGAN)
* [txt2imghd](https://github.com/jquesnelle/txt2imghd) - Fork of progrock diffusion that creates detailed, higher-resolution images by first generating an image from a prompt, upscaling it, then running img2img on smaller pieces of the upscaled image, and blending the results back into the original image.
* [neonsecret/stable-diffusion](https://github.com/neonsecret/stable-diffusion) - Fork focusing on bigger resolutions with less vram at the expense of speed, automatically adjusting to the GPUs abilities. Also includes upscaling, facial restoration via CodeFormer and [custom UI](https://github.com/neonsecret/stable-diffusion/blob/main/GUI_TUTORIAL.md)
* [stable-diffusion-jupyterlab-docker](https://github.com/pieroit/stable-diffusion-jupyterlab-docker) - A Docker setup ready to go with Jupyter notebooks for Stable Diffusion.
* [runwayml/stable-diffusion](https://github.com/runwayml/stable-diffusion) - Stable Diffusion Branch by [RunwayML](https://runwayml.com) with specifically trained inpainting model for high quality inpainting.
Checkpoints (.ckpt files) must be separately downloaded and are required to run Stable Diffusion. The latest model release is v1.5 released by runwayml. The latest stability ai release is 1.4.
* 🖊️ [Official Model Card](https://huggingface.co/CompVis/stable-diffusion) - Official Stability AI Model Card on Hugging Face with all versions of the model. Download requires sign-in and acceptance of terms of service.
* [stable-diffusion-v-1-4-original.chkpt](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original) - The original 1.4 model's card
* [RealESRGAN Models](https://github.com/xinntao/Real-ESRGAN/releases/) - Download location for the latest RealESRGAN models required to use the upscaling features implemented by many forks. Different models exist for realistic and anime content. Please refer to the fork documentation to identify the ones you
* [sd-v1-5-inpainting from RunwayML](https://huggingface.co/runwayml/stable-diffusion-inpainting/blob/main/sd-v1-5-inpainting.ckpt) - Checkpoint optimized for inpainting on SD 1.5, released by runwayML.
* 🖊️💵 [Offical Colab](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/stable_diffusion.ipynb) - The official, optimized colab for running SD on Google Cloud. Due to VRAM requirements required Colab Pro to create images.
* [Deforum](https://github.com/deforum/stable-diffusion) - Advanced notebook for Stable Diffusion with 2D, 3D, Video Input, and Interpolation animations. Includes inpainting, prompt batching, and more.
* 🖊️ [Stable Diffusion Interpolation](https://colab.research.google.com/drive/1EHZtFjQoRr-bns1It5mTcOVyZzZD9bBc?usp=sharing) - AA simple implementation of generating N interpolated images (Colab)
* [huggingface/diffuse-the-rest](https://huggingface.co/spaces/huggingface/diffuse-the-rest) - Diffuse the Rest - img2img from simple sketches or uploaded images.
* [Prompt to Prompt](https://github.com/bloc97/CrossAttentionControl) - Unofficial Implementation of Cross-attention-control for prompt to prompt image editing.
* [sd-prompt-graph](https://github.com/trevbook/sd-prompt-graph) - This is a React-based curve editor GUI for prompt interpolation animations made with Stable Diffusion.
* [Dreambooth-Stable-Diffusion](https://github.com/XavierXiao/Dreambooth-Stable-Diffusion) - Implementation of [Google's DreamBooth](https://arxiv.org/abs/2208.12242) for stable diffusion, allowing fine-tuning of the model for specific concepts.
* [textual-inversion](https://github.com/rinongal/textual_inversion) - Addition of personalized content to Stable Diffusion without retraining the model ([Paper](https://textual-inversion.github.io/), [Paper2](https://dreambooth.github.io/)).
* [sd-concepts-library](https://huggingface.co/sd-concepts-library) - A library of user created [textual-inversion](https://textual-inversion.github.io/) embeddings to add new concepts to stable diffusion
* [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) - Gradio based UI with extensive features such as in and outpainting, previews, xy plots, upscaling, clip-interrogation, textual inversion, negative prompting, a variety of upscaling features, checkpoint merging and switching capabilities and more. Comes with a handy install script that takes care of most dependencies and addons.
* 🖊️💵 [Auto SD Workflow](https://www.patreon.com/auto_sd_workflow) - A UI for [lstein/stable-diffusion](https://github.com/lstein/stable-diffusion)'s dream.py with optimized UX for large-scale/production workflow around image synthesis. [Video Walkthrough](https://vimeo.com/748114237).
* 🖊️ [DiffusionUI](https://github.com/leszekhanusz/diffusion-ui) - web UI made with Vue.js inspired by Dall-e using [diffusers](https://github.com/huggingface/diffusers), perfect for inpainting. [Video demo](https://www.youtube.com/watch?v=AFZvW5qURes)
* 🖊️ [KIRI.ART](https://kiri.art/) (formerly SD-MUI) - mobile-first PWA with multiple models (incl. waifu diffusion). Run free locally or use free & paid credits on the live site. Built with React + MaterialUI. ([Source Code](https://github.com/gadicc/stable-diffusion-react-nextjs-mui-pwa)) `MIT License``TypeScript`
* [sd-webui/stable-diffusion-webui](https://github.com/sd-webui/stable-diffusion-webui) - Very active fork with optional, highly featureful Gradio UI and support for txt2img, img2img inpainting, GFPGAN, ESRGAN, weighted prompts, optimized low memory version, optional [textual-inversion](https://textual-inversion.github.io/) and more.
* [Stable Diffusion Infinity](https://github.com/lkwq007/stablediffusion-infinity) - A proof of concept for outpainting with an infinite canvas interface. (requires powerful GPU).
* [stable-diffusion-webui-docker](https://github.com/AbdBarho/stable-diffusion-webui-docker) - A docker based frontend integrating the most popular forks.
* [jquesnelle/txt2imghd](https://github.com/jquesnelle/txt2imghd) - A port of the GOBIG mode from progrockdiffusion, providing high quality upscaling on top of txt2img.
* [lama-cleaner](https://github.com/Sanster/lama-cleaner) - Content aware AI inpainting tool useful for removing unwanted objects or defects from images. Python: ```pip install lama-cleaner```
* [GFPGAN](https://github.com/TencentARC/GFPGAN) - Face Restoration GAN included in several forks for automatically fixing the face deformation commonly found in SD output.
* [CodeFormer](https://github.com/sczhou/CodeFormer) - Another Face Restoration model ([Paper](https://arxiv.org/abs/2206.11253)).
* [ai-art-generator](https://github.com/rbbrdckybk/ai-art-generator) - AI art generation suite combining Stable Diffusion and other models for high volume art generation.
* [dfserver](https://github.com/huo-ju/dfserver) distributed backend AI pipeline server for building self-hosted distributed GPU cluster to run the Stable Diffusion and various AI image or prompt building model.
* [pharmapsychotic/clip-interrogator](https://github.com/pharmapsychotic/clip-interrogator) - Jupyter notebook uses CLIP models to suggest a prompt for images similar to a given image ([Demo](https://replicate.com/methexis-inc/img2prompt)).
* [rom1504/clip-retrieval](https://github.com/rom1504/clip-retrieval) - Searches for prompt keywords in the datasets used in training Stable Diffusion and other models ([Online GUI](https://rom1504.github.io/clip-retrieval/)). Some GUIS like Automatic1111 include this functionality.
* [Stable Diffusion Prompt Generator](https://huggingface.co/Gustavosta/MagicPrompt-Stable-Diffusion) - Gives suggestions for improving a given text prompt.
* [stable-dreamfusion](https://github.com/ashawkey/stable-dreamfusion) - An open source implementation of Google's text-to-3D dreamfusion paper with imagegen replaced by stable diffusion.
* [Stable Diffusion How To](https://www.assemblyai.com/blog/how-to-run-stable-diffusion-locally-to-generate-images/) - A basic tutorial on getting Stable Diffusion up and running.
* [Installing on Windows](https://rentry.org/SDInstallation) - A guide on installing and runing Stable Diffusion on Windows.
* [Running on M1 Apple Silicon](https://www.reddit.com/r/StableDiffusion/comments/wx0tkn/stablediffusion_runs_on_m1_chips/) - Reddit thread with instructions on running Stable Diffusion on Apple M1 CPU and GPU.
* [Easy CPU-only Stable Diffusion](https://rentry.org/cpu_stable_diffusion_guide) - A guide on setting up CPU-only Stable Diffusion for GNU/Linux without littering the system with dependencies.
* [Stable Diffusion Akashic Records](https://github.com/Maks-s/sd-akashic) - A comprehensive curated list of guides, studies, keywords, prompts and artists.
* [AI Image Generator Comparison](https://petapixel.com/2022/08/22/ai-image-generators-compared-side-by-side-reveals-stark-differences/) - A visual comparison between Dall-e, Stable Diffusion and Midjourney by PetaPixel.com.
* [Getting great results at Stable Diffusion](https://old.reddit.com/r/StableDiffusion/comments/x41n87/how_to_get_images_that_dont_suck_a/) - A guide on generating images that don't suck.
* [Practical deep learning for coders](https://course.fast.ai/) - high quality course by fast.ai aimed at coders that covers many aspects of deep learning, including stable-diffusion.
* [Modifier Studies](https://proximacentaurib.notion.site/2b07d3195d5948c6a7e5836f9d535592?v=b5b75a67cc52483c9965cfc141f6f582) - Visual study of popular modifiers/keywords.
* [Artist Studies](https://remidurant.com/artists/#) - Visual study of various artists.
* [Building a SD Discord Bot](https://replicate.com/blog/build-a-robot-artist-for-your-discord-server-with-stable-diffusion) - A tutorial on building a Stable Diffusion Discord bot using Python.
* [1 week of Stable Diffusion](https://multimodal.art/news/1-week-of-stable-diffusion) - A curated list of Stable Diffusion services, adaptations, user interfaces and integrations.
* [pharmapsychotic.com/tools](https://pharmapsychotic.com/tools.htm) - A curated list of Tools and Resources for AI Art, including but not limited to Stable Diffusion.
* [Stable Diffusion Resources](https://stackdiary.com/stable-diffusion-resources/) - A thorough resource for answering pressing questions about Stable Diffusion, including guides, tutorials, and best software.
* 🖊️💵 [AI Art Generator (IOS)](https://apps.apple.com/app/apple-store/id1644315225?pt=94765902&ct=github&mt=8) - iOS App to generate art using Stable Diffusion.
* 🖊️💵 [Dream Studio](http://beta.dreamstudio.ai/) - Online art generation service by StabilityAI, the creators of Stable Diffusion. Similar to services like DALL-E or Midjourney, this operates on a credit model with a free allowance of credits given to signed up users on a monthly basis.
* 🖊️💵 [dream.ai](https://www.dream.ai/) - Online art generation service by Wombo.ai (mobile apps available).
* 🖊️💵 [Starry AI (IOS)](https://apps.apple.com/us/app/starryai-create-art-with-ai/id1580512844) - Another IOS app offering stable diffusion with preset art styles.
* 🖊️ [Stable Horde](https://stablehorde.net/) - Distributed stable diffusion cluster (think folding@home) with web, discord and telegram interfaces where joining with your GPU gives you priority.