Repetition

What is Repetition?

Repetition is repeating the same word or similar phrases within a prompt. This technique can cause the model to emphasize that word in the generated image.

An Example of Repetition in Image Prompting

@Phillip Isola generated these waterfalls with DALLE:

A beautiful painting of a mountain next to a waterfall..

A very very very very very very very very very very very very very very very very very very very very very very beautiful painting of a mountain next to a waterfall.

The emphasis on the word very seems to improve generation quality! Repetition can also be used to emphasize subject terms. For example, if you want to generate an image of a planet with aliens, using the prompt A planet with aliens aliens aliens aliens aliens aliens aliens aliens aliens aliens aliens aliens will make it more likely that aliens are in the resultant image. The following images are made with Stable Diffusion.

A planet with aliens

A planet with aliens aliens aliens aliens aliens aliens aliens aliens aliens aliens aliens aliens

Conclusion

Repetition of a word or similar phrase can be used to emphasize the most important aspects of an image prompt and is therefore a useful technique in generating AI images.

FAQ

Why is repetition useful in image prompting?

As demonstrated in this article, repetition of a certain word (or similar phrases) can increase the likelihood of the generated output adhering to the instructions in the prompt.

Notes

This method is not perfect, and using weights (next article) is often a better option.

Sander Schulhoff

Sander Schulhoff is the Founder of Learn Prompting and an ML Researcher at the University of Maryland. He created the first open-source Prompt Engineering guide, reaching 3M+ people and teaching them to use tools like ChatGPT. Sander also led a team behind Prompt Report, the most comprehensive study of prompting ever done, co-authored with researchers from the University of Maryland, OpenAI, Microsoft, Google, Princeton, Stanford, and other leading institutions. This 76-page survey analyzed 1,500+ academic papers and covered 200+ prompting techniques.

Footnotes

1. Oppenlaender, J. (2022). A Taxonomy of Prompt Modifiers for Text-To-Image Generation. ↩