Book

Transformers for Natural Language Processing

Being the first book in the market to dive deep into the Transformers, this book is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers with Python, PyTorch, and TensorFlow

Offered byPackt Logo

Difficulty Level

Intermediate

Completion Time

20h4m

Language

English

About Book

Who Is This Book For?

If you want to learn about and apply transformers to your natural language (and image) data, this book is for you. You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community to help guide you on your transformers journey!

Book content

chapters 20h4m total length

What are Transformers?

Getting Started with the Architecture of the Transformer Model

Fine-Tuning BERT Models

Pretraining a RoBERTa Model from Scratch

Downstream NLP Tasks with Transformers

Machine Translation with the Transformer

The Rise of Suprahuman Transformers with GPT-3 Engines

Applying Transformers to Legal and Financial Documents for AI Text Summarization

Matching Tokenizers and Datasets

Semantic Role Labeling with BERT-Based Transformers

Let Your Data Do the Talking: Story, Questions, and Answers

Detecting Customer Emotions to Make Predictions

Analyzing Fake News with Transformers

Interpreting Black Box Transformer Models

From NLP to Task-Agnostic Transformer Models

The Emergence of Transformer-Driven Copilots

The Consolidation of Suprahuman Transformers with OpenAI’s ChatGPT and GPT-4'

Appendix I — Terminology of Transformer Models

Appendix II — Hardware Constraints for Transformer Models

Appendix III — Generic Text Completion with GPT-2

Appendix IV — Custom Text Completion with GPT-2

Appendix V — Answers to the Questions

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