Prompt Engineering Guide
😃 Basics
💼 Applications
🧙‍♂️ Intermediate
🤖 Đại lý
⚖️ Reliability
🖼️ Image Prompting
🔓 Prompt Hacking
🔨 Tooling
💪 Prompt Tuning
🎲 Miscellaneous
Models
📙 Vocabulary Reference
📚 Bibliography
📦 Prompted Products
🛸 Additional Resources
🔥 Hot Topics
✨ Credits
🖼️ Image Prompting🟢 Weighted Terms

Weighted Terms

🟢 This article is rated easy
Reading Time: 1 minute
Last updated on August 7, 2024

Sander Schulhoff

Some models (Stable Diffusion, Midjourney, etc.) allow you to weight terms in a prompt. This can be used to emphasize certain words or phrases in the generated image. It can also be used to de-emphasize certain words or phrases in the generated image. Let's consider a simple example:

Example

Here are a few mountains generated by Stable Diffusion, with the prompt mountain.

However, if we want mountains without trees, we can use the prompt mountain | tree:-10. Since we weighted tree very negatively, they do not appear in the generated image.

Weighted terms can be combined into more complicated prompts, like A planet in space:10 | bursting with color red, blue, and purple:4 | aliens:-10 | 4K, high quality

Notes

Read more about weighting in some of the resources at the end of this chapter.

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.