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Prompt Engineering Best Practices: Text Expansion
Data Science   Latest   Machine Learning

Prompt Engineering Best Practices: Text Expansion

Last Updated on March 26, 2024 by Editorial Team

Author(s): Youssef Hosni

Originally published on Towards AI.

Prompt Engineering for Instruction-Tuned LLMs

Text expansion is the task of taking a shorter piece of text, such as a set of instructions or a list of topics, and having the large language model generate a longer piece of text, such as an email or an essay about some topic.

There are some great uses of this, such as if you use a large language model as a brainstorming partner. However, there are also some problematic use cases of this, such as if someone were to use it, they generate a large amount of spam.

In this article, we’ll go through an example of how you can use a language model to generate a personalized email based on some information. The email is self-proclaimed to be from an AI bot which is very important.

We’re also going to use another one of the model’s input parameters called “temperature” which allows you to vary the kind of degree of exploration and variety in the kind of model’s responses. So let’s get into it!

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Published via Towards AI

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