Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
AI magics meet Infinite draw board.
| Date | Stars |
|---|---|
| 2026-07-24 | 1936 |
| 2026-07-25 | 1936 |
| 2026-07-28 | 1936 |
| 2026-07-30 | 1936 |
| 2026-08-06 | 1936 |
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growth rate 0.00%/day
 An open sourced, AI-powered creator for everyone. > * This is the backend project of the `Creator` product. If you are looking for the **WebUI** codes, you may checkout the [`carefree-drawboard`](https://github.com/carefree0910/carefree-drawboard) 🎨 project. > > * Most of the contents have been moved to the [Wiki](https://github.com/carefree0910/carefree-creator/wiki) page. <div align="center"> ### [Wiki](https://github.com/carefree0910/carefree-creator/wiki) | [WebUI Codes](https://github.com/carefree0910/carefree-drawboard) <div align="left"> # Installation `carefree-creator` is built on top of `carefree-learn`, and requires: - `Python>=3.8` - `pytorch>=1.12.0`. Please refer to [PyTorch](https://pytorch.org/get-started/locally/)'s official website, and it is highly recommended to pre-install PyTorch with conda. ## Hardware Requirements > Related issue: [#10](https://github.com/carefree0910/carefree-creator/issues/10). This project will eat up 11~13 GB of GPU RAM if no modifications are made, because it actually integrates FIVE different SD versions together, and many other models as well. 🤣 There are two ways that can reduce the usage of GPU RAM - lazy loading and partial loading, see the following [`Run`](#run) section for more details. ## pip installation ```bash pip install carefree-creator ``` If you are interested in the latest features, you may use `pip` to install from source as well: ```bash git clone https://github.com/carefree0910/carefree-creator.git cd carefree-creator pip install -e . ``` ### Run `carefree-creator` builds a CLI for you to setup your local service. For instance, we can: ```bash cfcreator serve ``` If you don't have an NVIDIA GPU (e.g. mac), you may try: ```bash cfcreator serve --cpu ``` If you are using your GPU-powered laptop, you may try: ```bash cfcreator serve --limit 1 ``` > The `--limit` flag is used to limit the number of loading models. By specifying `1`, only the executing model will be loaded, and other models will stay on your disk. > > See [#10](https://github.com/carefree0910/carefree-creator/issues/10#issuecomment-1520661893) for more details. If you have plenty of RAM resources but your GPU RAM is not large enough, you may try: ```bash cfcreator serve --lazy ``` > With the `--lazy` flag, the models will be loaded to RAM, and only the executing model will be moved to GPU RAM. > > So as an exchange, your RAM will be eaten up! 🤣 If you only want to try the SD basic endpoints, you may use: ```bash cfcreator serve --focus sd.base ``` And if you only want to try the SD anime endpoints, you may use: ```bash cfcreator serve --focus sd.anime ``` More usages could be found by: ```bash cfcreator serve --help ``` ## Docker ### Prepare ```bash export TAG_NAME=cfcreator git clone https://github.com/carefree0910/carefree-creator.git cd carefree-creator ``` ### Build ```bash docker build -t $TAG_NAME . ``` If your internet environment lands in China, it might be faster to build with `Dockerfile.cn`: ```bash docker build -t $TAG_NAME -f Dockerfile.cn . ``` ### Run ```bash docker run --gpus all --rm -p 8123:8123 $TAG_NAME:latest ``` # Credits - [Stable Diffusion](https://github.com/CompVis/stable-diffusion), the foundation of various generation methods. - [Stable Diffusion from runwayml](https://github.com/runwayml/stable-diffusion), the adopted SD-inpainting method. - [Waifu Diffusion](https://github.com/harubaru/waifu-diffusion), the anime-finetuned version of Stable Diffusion. - [Real ESRGAN](https://github.com/xinntao/Real-ESRGAN), the adopted Super Resolution methods. - [Latent Diffusion](https://github.com/CompVis/latent-diffusion), the adopted Inpainting & Landscape Synthesis method. - [carefree-learn](https://github.com/carefree0910/carefree-learn), the code base that has re-implemented all the models above and provided clean and handy APIs. - And You! Thank you for watching!
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:64102008cdc7be30, topic:stable-diffusion, topic:text-to-image, topic:inpainting