Mastering Transformers, Second Edition

Mastering Transformers, 2nd Edition

eBook Details:

  • Paperback: 462 pages
  • Publisher: WOW! eBook; 2nd edition (June 3, 2024)
  • Language: English
  • ISBN-10: 1837633789
  • ISBN-13: 978-1837633784

eBook Description:

Mastering Transformers, Second Edition: The Journey from BERT to Large Language Models and Stable Diffusion. Explore transformer-based language models from BERT to GPT, delving into NLP and computer vision tasks, while tackling challenges effectively.

Transformer-based language models such as BERT, T5, GPT, DALL-E, and ChatGPT have dominated NLP studies and become a new paradigm. Thanks to their accurate and fast fine-tuning capabilities, transformer-based language models have been able to outperform traditional machine learning-based approaches for many challenging natural language understanding (NLU) problems.

Aside from NLP, a fast-growing area in multimodal learning and generative AI has recently been established, showing promising results. Mastering Transformers will help you understand and implement multimodal solutions, including text-to-image. Computer vision solutions that are based on transformers are also explained in the book. You’ll get started by understanding various transformer models before learning how to train different autoregressive language models such as GPT and XLNet. The Mastering Transformers, 2nd Edition book will also get you up to speed with boosting model performance, as well as tracking model training using the TensorBoard toolkit. In the later chapters, you’ll focus on using vision transformers to solve computer vision problems. Finally, you’ll discover how to harness the power of transformers to model time series data and for predicting.

  • Focus on solving simple-to-complex NLP problems with Python
  • Discover how to solve classification/regression problems with traditional NLP approaches
  • Train a language model and explore how to fine-tune models to the downstream tasks
  • Understand how to use transformers for generative AI and computer vision tasks
  • Build transformer-based NLP apps with the Python transformers library
  • Focus on language generation such as machine translation and conversational AI in any language
  • Speed up transformer model inference to reduce latency

By the end of this Mastering Transformers, Second Edition book, you’ll have an understanding of transformer models and how to use them to solve challenges in NLP and CV.

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