Google Colab quick start Stable Diffusion Webui
Colab is a product developed by the Google Research team. In Colab, anyone can write and execute any Python code through their browser. It is particularly suitable for machine learning, data analysis, and educational purposes. Technically, Colab is a hosted Jupyter notebook service. It is worth noting that in Colab development, there is no need to worry about any configuration, and you can use CPU, GPU, and other environments that are not available locally for free.
1.First, you need a Google account to log in to Google Chrome.
2.Open Github：stable-diffusion-webui-colab , which is a GitHub repository containing stable versions, latest versions, and lightweight versions of Stable Diffusion WebUI.
3.Find the version you want to use. You can use the shortcut key CTRL+F to search, and then enter anything-v3.0 to quickly locate the specific model. After locating the model, pay attention to the labels in the first three columns of the README table. These labels represent different versions: lite, stable, and nightly.
The lite version has a stable WebUI and a stable installed extension.
The stable version has ControlNet, stable WebUI, and stable installed extensions.
The nightly version has ControlNet, the latest WebUI, and daily installed extension updates.
4.Click on the corresponding label. Here we choose to experience the nightly version, and then it will jump to the Google Colab code editing and running window, as shown in the figure below:
5.Click the start button in the upper left corner of the code running window, and it will be automatically deployed. Wait for about ten minutes (at the slowest), and finally, four links will be output. You can choose any of these links and access them in your browser. These links are temporary and need to be redeployed every time you use them.
6.When accessing the link, you will see a WebUI interface, where you can experiment with various AI tasks such as txt2img and image2img. Select the corresponding task on the left, enter the relevant parameters, and click run to get the results. There are also model download, model save, model training, and other functions in the upper right corner of the interface.
In summary, using Google Colab to quickly deploy Stable Diffusion WebUI is very convenient. You can conduct various AI graphics tasks on it and train and test your own models. At the same time, it should be noted that since the resources the resources allocated are temporary and limited. Please close them after you finish using them. If you do not close the idle time, the GPU resources allocated by Colab will be wasted, and then your account will not be able to experience the GPU.