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Building LLM Powered  Applications

You're reading from   Building LLM Powered Applications Create intelligent apps and agents with large language models

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835462317
Length 342 pages
Edition 1st Edition
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Author (1):
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Valentina Alto Valentina Alto
Author Profile Icon Valentina Alto
Valentina Alto
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Table of Contents (16) Chapters Close

Preface 1. Introduction to Large Language Models FREE CHAPTER 2. LLMs for AI-Powered Applications 3. Choosing an LLM for Your Application 4. Prompt Engineering 5. Embedding LLMs within Your Applications 6. Building Conversational Applications 7. Search and Recommendation Engines with LLMs 8. Using LLMs with Structured Data 9. Working with Code 10. Building Multimodal Applications with LLMs 11. Fine-Tuning Large Language Models 12. Responsible AI 13. Emerging Trends and Innovations 14. Other Books You May Enjoy
15. Index

Summary

This chapter covered some of the most promising LLMs in the market. It first differentiated between proprietary and open-source models, with all the related pros and cons. It then offered a deep dive into the architecture and technical features of GPT-4, PaLM-2, Claude 2, LLaMa-2, Falcon LLM, and MPT, with the addition of a section covering some LMMs. Finally, it provided a light framework to help developers decide which LLMs to pick while building AI-powered applications. This is pivotal to get the greatest impact from your application, given your industry-specific scenario.

Starting from the next chapter, we will start working hands-on with LLMs within applications.

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