Book Image

Transformers for Natural Language Processing - Second Edition

By : Denis Rothman
5 (1)
Book Image

Transformers for Natural Language Processing - Second Edition

5 (1)
By: Denis Rothman

Overview of this book

Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs? Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses. You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model. If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides. The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details). You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using DALL-E 2, ChatGPT, and GPT-4. By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective.
Table of Contents (25 chapters)
18
Other Books You May Enjoy
19
Index
Appendix I — Terminology of Transformer Models

Summary

In this chapter, we built on the knowledge and expertise you acquired in the previous chapters to tackle OpenAI’s state-of-the-art transformer models.

The knowledge you now possess enables you to make an incremental step forward from the GPT-3 model you already discovered in Chapter 7, The Rise of Suprahuman Transformers with GPT-3 Engines. For those who are beginning to learn transformers now, the path will be quite long.

We first jump-started ChatGPT using the same approach as in Chapter 7. The new step was to implement a conversational AI prompt. You saw how ChatGPT Plus can generate a k-means clustering classification program, plot the outputs, and provide explanations.

Getting started with GPT-4 was an incremental step forward in implementing a powerful general-purpose transformer model.

Model exploration took you into the world of 50+ transformer models, including davinci, GPT-3.5-turbo, and GPT-4.

Explainable AI by ChatGPT opened the OpenAI...