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Pretrain Vision and Large Language Models in Python

You're reading from   Pretrain Vision and Large Language Models in Python End-to-end techniques for building and deploying foundation models on AWS

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781804618257
Length 258 pages
Edition 1st Edition
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Author (1):
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Emily Webber Emily Webber
Author Profile Icon Emily Webber
Emily Webber
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Table of Contents (23) Chapters Close

Preface 1. Part 1: Before Pretraining
2. Chapter 1: An Introduction to Pretraining Foundation Models FREE CHAPTER 3. Chapter 2: Dataset Preparation: Part One 4. Chapter 3: Model Preparation 5. Part 2: Configure Your Environment
6. Chapter 4: Containers and Accelerators on the Cloud 7. Chapter 5: Distribution Fundamentals 8. Chapter 6: Dataset Preparation: Part Two, the Data Loader 9. Part 3: Train Your Model
10. Chapter 7: Finding the Right Hyperparameters 11. Chapter 8: Large-Scale Training on SageMaker 12. Chapter 9: Advanced Training Concepts 13. Part 4: Evaluate Your Model
14. Chapter 10: Fine-Tuning and Evaluating 15. Chapter 11: Detecting, Mitigating, and Monitoring Bias 16. Chapter 12: How to Deploy Your Model 17. Part 5: Deploy Your Model
18. Chapter 13: Prompt Engineering 19. Chapter 14: MLOps for Vision and Language 20. Chapter 15: Future Trends in Pretraining Foundation Models 21. Index 22. Other Books You May Enjoy

Other generative modalities

Since the 2022 ChatGPT moment, most of the technical world has been fascinated by the proposition of generating novel content. While this was always somewhat interesting, the meeting of high-performance foundation models with an abundance of media euphoria over the capabilities, combined with a post-pandemic community with an extremely intense fear of missing out, has led us to the perfect storm of a global fixation on generative AI.

s this a good thing? Honestly, I’m happy to finally see the shift; I’ve been working on generating content with AI/ML models in some fashion since at least 2019, and as a writer and creative person myself, I’ve always thought this was the most interesting part of machine learning. I was very impressed by David Foster’s book (3) on the topic. He’s just published an updated version of this to include the latest foundation models and methods! Let’s quickly recap some other types of modalities...

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