- 中图分类号: TP1
- 语种: ENG
- 出版信息: Packt Publishing 2022 603页
- EISBN: 9781803243481
- PISBN-P: 9781803247335
- 原文访问地址:
KG评星
知识图谱评星,是一种基于用户使用的评价体系,综合图书的评论数量、引文数量、Amazon评分以及图谱网络中节点的PageRank值(即考虑相邻节点数量和重要性)等多种因素计算而得出的评价数值。星级越高,推荐值越高。CAT核心级
核心学术资源(CAR)项目作为教图公司推出的一项知识型服务,旨在打造一套科学、有效的图书评价体系,并协助用户制定相应的馆藏建设方案。CAR项目调查和分析12所世界一流大学的藏书数据,以收藏学校的数量确定书目的核心级,核心级越高,代表书目的馆藏价值越高。选取核心级在三级以上,即三校以上共藏的图书作为核心书目(CAT)。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.Purchase of the print or Kindle book includes a free eBook in PDF formatKey Features: * Improve your productivity with OpenAI’s ChatGPT and GPT-4 from prompt engineering to creating and analyzing machine learning models * Pretrain a BERT-based model from scratch using Hugging Face * Fine-tune powerful transformer models, including OpenAI's GPT-3, to learn the logic of your dataBook Description: Transformers are...well...transforming the world of AI. There are many platforms and models out there, but which ones best suit your needs?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.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.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.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).You'll see how cutting-edge platforms, such as OpenAI, have taken transformers beyond language into computer vision tasks and code creation using DALL-E 2, ChatGPT, and GPT-4.By the end of this book, you'll know how transformers work and how to implement them and resolve issues like an AI detective.What you will learn: * Discover new techniques to investigate complex language problems * Compare and contrast the results of GPT-3 against T5, GPT-2, and BERT-based transformers * Carry out sentiment analysis, text summarization, casual speech analysis, machine translations, and more using TensorFlow, PyTorch, and GPT-3 * Find out how ViT and CLIP label images (including blurry ones!) and create images from a sentence using DALL-E * Learn the mechanics of advanced prompt engineering for ChatGPT and GPT-4Who this book is for: If you want to learn about and apply transformers to your natural language (and image) data, this book is for you.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 to help guide you on your transformers journey!