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

ChatGPT Plus writes and comments on a program

In this section, ChatGPT Plus will do all the work: writing the code, commenting on the code, and providing an explanation.

IBM SPSS Decision Trees is a classification and decision tree tool designed for a decision-making system: https://www.ibm.com/products/spss-decision-trees.

However, for some projects, we do not need a complex program but a compact function to get the job done.

Open the following notebook, Chapter17, which is in the GitHub repository:

ChatGPT_Plus_writes_and_explains_classification.ipynb

Install and import OpenAI and enter the API key before running the notebook.

Designing the prompt

After installing scikit-learn as suggested by ChatGPT Plus, we submit two requests in sequence to ChatGPT Plus:

  1. Provide a scikit-learn classification of the Iris dataset with some kind of matplotlib graph to describe the result. Don’t use OpenAI APIs.
  2. Now write a detailed explanation...