📝Definitions
Remember, the best way to learn is still through practice and experimentation!
Last updated
Remember, the best way to learn is still through practice and experimentation!
Last updated
A description of your image - more detailed descriptions will result in more detailed and accurate images.
An argument that instructs the model not to include certain things in the generated image.
A model defines, in simple terms, the style of the resulting image.
-> Same prompt, different models.
How many times to improve the generated image iteratively; higher values take longer; very low values can produce bad results. Notice how, in the example below, the image overall doesn't change too much anymore after only 15 steps. The recommended value to this parameter sits around 20 to 30 steps, any more than this and you start getting into diminishing returns territory.
-> Steps from 1 through 50.
Classifier Free Guidance Scale - how strongly the image should conform to the prompt - lower values produce more creative results - values too low might destroy coherency. Keep this value above 5 and below 15, recommended 7, if you aren't sure what value to use.
-> CFG Scale from 0 through 20.
A seed controls the output of a random number generator. The same seed (and parameters) will generate the same image. Not specifying a seed, or rerolling, randomizes the seed.
-> Same parameters, random seeds.
