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Generative AI with Python and TensorFlow 2

You're reading from   Generative AI with Python and TensorFlow 2 Create images, text, and music with VAEs, GANs, LSTMs, Transformer models

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800200883
Length 488 pages
Edition 1st Edition
Languages
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Authors (2):
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Raghav Bali Raghav Bali
Author Profile Icon Raghav Bali
Raghav Bali
Joseph Babcock Joseph Babcock
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Joseph Babcock
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Table of Contents (16) Chapters Close

Preface 1. An Introduction to Generative AI: "Drawing" Data from Models 2. Setting Up a TensorFlow Lab FREE CHAPTER 3. Building Blocks of Deep Neural Networks 4. Teaching Networks to Generate Digits 5. Painting Pictures with Neural Networks Using VAEs 6. Image Generation with GANs 7. Style Transfer with GANs 8. Deepfakes with GANs 9. The Rise of Methods for Text Generation 10. NLP 2.0: Using Transformers to Generate Text 11. Composing Music with Generative Models 12. Play Video Games with Generative AI: GAIL 13. Emerging Applications in Generative AI 14. Other Books You May Enjoy
15. Index

GPT 1, 2, 3…

OpenAI is an AI research group that has been in the spotlight for quite some time because of their newsworthy works such as GPT, GPT-2, and the recently released GPT-3. In this section, we will walk through a brief discussion related to these architectures and their novel contributions. Toward the end, we will use a pre-trained version of GPT-2 for our task of text generation.

Generative pre-training: GPT

The first model in this series is called GPT, or Generative Pre-Training. It was released in 2018, about the same time as the BERT model. The paper11 presents a task-agnostic architecture based on the ideas of transformers and unsupervised learning. The GPT model was shown to beat several benchmarks such as GLUE and SST-2, though the performance was overtaken by BERT, which was released shortly after this.

GPT is essentially a language model based on the transformer-decoder we presented in the previous chapter (see the section on Transformers). Since...

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