Wildcards in Stable Diffusion models serve as placeholders or variables that can be used to represent any value or range of values. They are particularly useful for pattern matching and data manipulation tasks. In the context of image synthesis and manipulation with Stable Diffusion, wildcards allow for flexible and dynamic generation of content. They can be used to specify certain attributes or elements in an image without being overly specific, enabling the model to fill in the details based on its training. This approach facilitates creativity and diversity in the generated images, as the wildcard can lead to a variety of results depending on how the model interprets it.

Wildcards is installed by default on RunDiffusion and is all set up and ready for use!

Wildcards Manager

The Wildcards manager is where you will access all your wildcard information. Below the search button will be your whole data set of wildcards. This includes the default wildcards as well as the ones you have imported.

Importing wildcards:

the directory as shown below is where you will place your wildcard.txt files

They should look like this when uploaded

Once you have the wildcards uploaded, it is as easy as searching through your data set and copy/paste the filename into your prompt within txt2img or img2img.

Wildcards are a fantastic way to increase your creativity and artistic style while generating Ai art. Below are a few links to Wildcard datasets to pull from.

Wildcards-for-SD/Wildcards/adj_chaos.txt at main · themartiantourist/Wildcards-for-SD
A wildcard database for Stable Diffusion. Contribute to themartiantourist/Wildcards-for-SD development by creating an account on GitHub.



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