Natural Language Processing With Transformers Building Language Applications With Hugging Face Epub
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Natural Language Processing with Transformers
Author: Lewis Tunstall
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2022-01-26
Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments
Natural Language Processing with Transformers
This Book grants Free Access to our e-learning Platform, which includes: ✅ Free Repository Code with all code blocks used in this book ✅ Access to Free Chapters of all our library of programming published books ✅ Free premium customer support ✅ Much more... Unlock the Full Potential of Transformers for Natural Language Processing and Beyond Transformers are reshaping the world of AI, powering innovations in natural language processing (NLP) and enabling groundbreaking multimodal applications. Whether you're an aspiring machine learning practitioner or an experienced developer, "Natural Language Processing with Transformers: Advanced Techniques and Multimodal Applications" is your definitive guide to mastering these cutting-edge models. What You'll Learn Dive into advanced NLP techniques: Explore machine translation, text summarization, sentiment analysis, named entity recognition, and more using state-of-the-art transformer architectures. Harness the Hugging Face ecosystem: Gain hands-on experience with tools and libraries that streamline model training, fine-tuning, and deployment. Build real-world solutions: Develop practical applications, including a sentiment analysis API and a custom NER pipeline, with detailed step-by-step instructions and code examples. Expand into multimodal AI: Discover how transformers integrate text, images, and video to power innovative use cases like medical image analysis and video summarization. Why This Book Stands Out Authored with clarity and precision, this book combines theoretical insights with practical guidance. Through hands-on projects, you'll learn to fine-tune models for domain-specific tasks, optimize them for real-world deployment, and explore multimodal AI's potential to revolutionize industries such as healthcare, education, and content creation. Who This Book Is For This book is perfect for: Machine learning enthusiasts looking to deepen their understanding of transformers. Data scientists and engineers seeking practical knowledge to build and deploy real-world applications. Academics and researchers exploring advanced NLP and multimodal techniques. Practical Projects to Solidify Your Learning Put theory into practice with projects that include: Creating a Named Entity Recognition pipeline fine-tuned for custom datasets. Building a scalable sentiment analysis API with FastAPI and Hugging Face models. Developing multimodal applications such as medical image-text integration and video summarization. Your Journey Into the Future of AI Starts Here Transform your skills and become a leader in NLP and multimodal AI. With "Natural Language Processing with Transformers: Advanced Techniques and Multimodal Applications", you'll gain the expertise needed to build impactful AI solutions that leverage the full power of transformer models.
Natural Language Processing with Transformers
Since their introduction in 2017, Transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or machine learning engineer, this practical book shows you how to train and scale these large models using HuggingFace Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf use a hands-on approach to teach you how Transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize Transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how Transformers can be used for cross-lingual transfer learning Apply Transformers in real-world scenarios where labeled data is scarce Make Transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train Transformers from scratch and learn how to scale to multiple GPUs and distributed environments