We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Due to their ease of use, large language models (LLMs) have seen an explosive rise to popularity. By just crafting a textual prompt, even those who are completely unfamiliar with deep learning can leverage massive neural networks to quickly solve a wide variety of complex problems. Over time, these models have become even easier to use via improved instruction following capabilities and alignment. However, effectively prompting LLMs is both an art and a science—significant performance improvements can be achieved by slightly tweaking our prompting implementation or strategy. In this overview, we will develop a comprehensive understanding of prompt engineering, beginning with basic concepts and going all the way to cutting-edge techniques that have been proposed in recent months.
continue reading on cameronrwolfe.substack.com
⚠️ This post links to an external website. ⚠️
If this post was enjoyable or useful for you, please share it! If you have comments, questions, or feedback, you can email my personal email. To get new posts, subscribe use the RSS feed.