If you want to play around with the image generating AI stable diffusion you can follow this guide. If you just want to start already, jump to the How section below.
This is just a launcher for AUTOMATIC1111 stable diffusion web ui using google colab.
AUTOMATIC1111 is currently the best web ui to work with stable diffusion.
This launcher runs in a single cell and uses google drive as your disk. This means your generations are saved to gdrive and next time you run it, it will not redownload anything, so it should start faster.
Also a random password is generated on each run, which makes it safer from getting hijacked by bots scanning gradio urls.
If this does not work for you or you prefer a notebook with a more active community, take a look at TheLastBen/fast-stable-diffusion
This is a very small and mostly too simple explanation of the things related to stable diffusion.
Artificial intelligence and machine learning are very broad concepts. The kind of machine learning that is making the news and revolutionizing content creation are neural networks.
Don't let the name fool you though, they are just a single math function that takes an input and produces an output, and there is a lot of constants inside it.
What is called training is basically getting a database of inputs and expected outputs, running this function over the input, measuring the difference between what came out of the function and what was expected and then tweaking all constants inside the function so the function output is closer to the expected output.
The model, the thing you download, is a file (or several files) containing those constants.
The main take away from this is, this AI is just a huge single function that needs a bunch of constants inside.
An AI that learned how to remove noise from images. Trained by taking an image, adding some noise and then using the noise image as input and the clear image as expected output. It also used an image already with noise, added even more noise and trained the AI with this, so the AI just tries to remove a little bit of noise per step.
The trick is that when you input any image it always tries to denoise it. That is how it generates images.
It is like when you look at the clouds and see shapes when there is nothing actually there.
The company that trained stable diffusion and released it for free. They have a paid online editor dreamstudio
The database used to train stable diffusion.
You can explore it here
A company that offers something like a github but for AI. You can host models, datasets and other things there. They also provide a library (transformes library) that make it suer simple to use the models (and other things) they are hosting.
Google has a service, including a free tier, where you can run code on machines with powerfull gpus.
Code is run using python notebooks.
This is a developer that created an web ui for stable diffusion. This is the ui adopted by most of the community. There are others, but tis is by far the most active.
Anyone can take the model and train a new model. The end result is usually a .ckpt file (stands for checkpoint).
Those are customized to behave differently, see for example this one trained on disney animations.
ControlNet is a neural network structure to control diffusion models by adding extra conditions.
In practice, gives you some new ways to control your outputs on img2img. It is better to look at the link to understand it.
By far, the best place to learn more about stable diffusion is this subreddit
You can run the image generation program on a machine from google with the free tier. It will require you to look at some logs and try to find an url on them, but it is basically pressing a button.
You will need a google account.
Create an account at huggingface
Create a token at https://huggingface.co/settings/tokens
Go to settings
Create a new token
Copy the token and run this colab, you will need to give it permission to access google drive.
The first run will take a long time as it will download the models on your gdrive.
The next time it will be faster, but still take a couple of minutes.
Rule of thumb, check if the console says downloading or shows a percentage.
Copy the password from the console.
Click on the link
Use the user as user and the password you copied from the console.
You should then see the webui
There is a cell for that.
There is a cell at the end that you can run to download the models and install the controlnet extension.