<p><strong>OpenAI's GPT-3, ChatGPT, GPT-4 and Hugging Face transformers for language tasks in one book. Get a taste of the future of transformers, including computer vision tasks and code writing and assistance.</strong></p><p><br></p><p><strong>Purchase of the print or Kindle book includes a free eBook in PDF format</strong></p><p><br></p><p><strong>Key Features:</strong></p><ul><li>Pretrain a BERT-based model from scratch using Hugging Face</li><li>Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your data</li><li>Perform root cause analysis on hard NLP problems</li></ul><p><br></p><p><strong>Book Description:</strong></p><p>Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs?</p><p><br></p><p>Transformers for Natural Language Processing, 2nd Edition, guides you through the world of transformers, highlighting the strengths of different models and platforms, while teaching you the problem-solving skills you need to tackle model weaknesses.</p><p><br></p><p>You'll use Hugging Face to pretrain a RoBERTa model from scratch, from building the dataset to defining the data collator to training the model.</p><p><br></p><p>If you're looking to fine-tune a pretrained model, including GPT-3, then Transformers for Natural Language Processing, 2nd Edition, shows you how with step-by-step guides.</p><p><br></p><p>The book investigates machine translations, speech-to-text, text-to-speech, question-answering, and many more NLP tasks. It provides techniques to solve hard language problems and may even help with fake news anxiety (read chapter 13 for more details).</p><p><br></p><p>You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using Codex.</p><p><br></p><p>By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective!</p><p><br></p><p><strong>What You Will Learn:</strong></p><ul><li>Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E</li><li>Discover new techniques to investigate complex language problems</li><li>Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers</li><li>Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3</li><li>Measure the productivity of key transformers to define their scope, potential, and limits in production</li></ul><p><br></p><p><strong>Who this book is for:</strong></p><p>If you want to learn about and apply transformers to your natural language (and image) data, this book is for you.</p><p><br></p><p>You'll need a good understanding of Python and deep learning and a basic understanding of NLP to benefit most from this book. Many platforms covered in this book provide interactive user interfaces, which allow readers with a general interest in NLP and AI to follow several chapters. And, don't worry if you get stuck or have questions; this book gives you direct access to our AI/ML community and author, Denis Rothman. So, he'll be there to guide you on your transformers journey!</p>