You're reading from Mastering Transformers The Journey from BERT to Large Language Models and Stable Diffusion

Product type Paperback

Published in Jun 2024

Publisher Packt

ISBN-13 9781837633784

Length 462 pages

Edition 2nd Edition

Languages

Python

Tools

BERT

Concepts

GPT/LLMs

Authors (2):

Savaş Yıldırım

Meysam Asgari- Chenaghlu

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Table of Contents (25) Chapters

Preface

1. Part 1: Recent Developments in the Field, Installations, and Hello World Applications

2. Chapter 1: From Bag-of-Words to the Transformers FREE CHAPTER

3. Chapter 2: A Hands-On Introduction to the Subject

4. Part 2: Transformer Models: From Autoencoders to Autoregressive Models

5. Chapter 3: Autoencoding Language Models

6. Chapter 4: From Generative Models to Large Language Models

7. Chapter 5: Fine-Tuning Language Models for Text Classification

8. Chapter 6: Fine-Tuning Language Models for Token Classification

9. Chapter 7: Text Representation

10. Chapter 8: Boosting Model Performance

11. Chapter 9: Parameter Efficient Fine-Tuning

12. Part 3: Advanced Topics

13. Chapter 10: Large Language Models

14. Chapter 11: Explainable AI (XAI) in NLP

15. Chapter 12: Working with Efficient Transformers

16. Chapter 13: Cross-Lingual and Multilingual Language Modeling

17. Chapter 14: Serving Transformer Models

18. Chapter 15: Model Tracking and Monitoring

19. Part 4: Transformers beyond NLP

20. Chapter 16: Vision Transformers

21. Chapter 17: Multimodal Generative Transformers

22. Chapter 18: Revisiting Transformers Architecture for Time Series

23. Index

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24. Other Books You May Enjoy

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Software/hardware covered in the book	Operating system requirements
Programming language: Python	Windows, macOS, or Linux
Libraries: `transformers`, `PyTorch`, `peft`, `trl`
Jupyter Notebook

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Note

This book contains a few screenshots which have been captured to show the overview of workflows and also the UI. Due to this, the content in this images may appear small at 100% zoom. Please check out the PDF copy provided with the book to zoom in for clearer images.

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Table of Contents (25) Chapters

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