Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Transformers

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

Arrow left icon
Product type Paperback
Published in Jun 2024
Publisher Packt
ISBN-13 9781837633784
Length 462 pages
Edition 2nd Edition
Languages
Tools
Concepts
Arrow right icon
Authors (2):
Arrow left icon
Savaş Yıldırım Savaş Yıldırım
Author Profile Icon Savaş Yıldırım
Savaş Yıldırım
Meysam Asgari- Chenaghlu Meysam Asgari- Chenaghlu
Author Profile Icon Meysam Asgari- Chenaghlu
Meysam Asgari- Chenaghlu
Arrow right icon
View More author details
Toc

Table of Contents (25) Chapters Close

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 24. Other Books You May Enjoy

Other Books You May Enjoy

If you enjoyed this book, you may be interested in these other books by Packt:

Transformers for Natural Language Processing and Computer Vision

Denis Rothman

ISBN: 978-1-80512-872-4

  • Learn how to pretrain and fine-tune LLMs
  • Learn how to work with multiple platforms, such as Hugging Face, OpenAI, and Google Vertex AI
  • Learn about different tokenizers and the best practices for preprocessing language data
  • Implement Retrieval Augmented Generation and rules bases to mitigate hallucinations
  • Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP
  • Create and implement cross-platform chained models, such as HuggingGPT
  • Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4V

Mastering NLP from Foundations to LLMs

Lior Gazit, Meysam Ghaffari

ISBN: 978-1-80461-918-6

  • Master the mathematical...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime