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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 β€œtemperature” 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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