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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 60 recipes for building powerful NLP solutions using Python and LLM libraries

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781803245744
Length 312 pages
Edition 2nd Edition
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Concepts
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Authors (2):
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Saurabh Chakravarty Saurabh Chakravarty
Author Profile Icon Saurabh Chakravarty
Saurabh Chakravarty
Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (13) Chapters Close

Preface 1. Chapter 1: Learning NLP Basics 2. Chapter 2: Playing with Grammar FREE CHAPTER 3. Chapter 3: Representing Text – Capturing Semantics 4. Chapter 4: Classifying Texts 5. Chapter 5: Getting Started with Information Extraction 6. Chapter 6: Topic Modeling 7. Chapter 7: Visualizing Text Data 8. Chapter 8: Transformers and Their Applications 9. Chapter 9: Natural Language Understanding 10. Chapter 10: Generative AI and Large Language Models 11. Index 12. Other Books You May Enjoy

Running an LLM to follow instructions

In this recipe, we will learn how to get an LLM to follow instructions via prompting. An LLM can be provided some context and asked to generate text based on that context. This is a very novel feature of an LLM. The LLM can be specifically instructed to generate text based on explicit user requirements. Using this feature expands the breadth of use cases and applications that can be developed. The context and the question to be answered can be generated dynamically and used in various use cases ranging from answering simple math problems to sophisticated data extraction from knowledge bases.

We will use the meta-llama/Meta-Llama-3.1-8B-Instruct model for this recipe. This model is built on top of the meta-llama/Meta-Llama-3.1-8B model and has been tuned to follow instructions via prompts.

Getting ready

It is required that the user create the necessary credentials on the Hugging Face site to ensure that the model is available to be used...

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