පිළිගනිමු
😃 ප්රාථමික
💼 Applications
🧙‍♂️ Intermediate
🤖 නියෝජිතයන්
⚖️ Reliability
🖼️ Image Prompting
🔓 Prompt Hacking
🔨 Tooling
💪 Prompt Tuning
🎲 Miscellaneous
Models
📙 Vocabulary Reference
📚 Bibliography
📦 Prompted Products
🛸 Additional Resources
🔥 Hot Topics
✨ Credits
🖼️ Image Prompting🟢 Quality Boosters

Quality Boosters

🟢 This article is rated easy
Reading Time: 1 minute

Last updated on August 7, 2024

Quality boosters are terms added to a prompt to improve certain non-style-specific qualities of the generated image. For example "amazing", "beautiful", and "good quality" are all quality boosters that can be used to improve the quality of the generated image.

Example

Recall from the other page the pyramids generated with DALLE, and the prompt pyramid.

Now take at pyramids generated with this prompt:

Astronaut

Prompt


A beautiful, majestic, incredible pyramid, 4K

These are much more scenic and impressive!

Here is a list of a number of quality boosters:

High resolution, 2K, 4K, 8K, clear, good lighting, detailed, extremely detailed, sharp focus, intricate, beautiful, realistic+++, complementary colors, high quality, hyper detailed, masterpiece, best quality, artstation, stunning

Notes

Similar to the note on the previous page, our working definition of quality boosters differs from Oppenlaender et al.. This being said, it is sometimes difficult to exactly distinguish between quality boosters and style modifiers.

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. 2

Copyright © 2024 Learn Prompting.