NATURAL LANGUAGE PROCESSING WITH TRANSFORMERS
TUNSTALL LEWIS
NATURAL LANGUAGE PROCESSING WITH TRANSFORMERS Building Language Applications with Hugging Face - SECOND EDITION - CALIFORNIA O'REILLY SPD PVT LTD 2023 - XXII 386P
NLP
"Natural Language Processing with Transformers," authored by Lewis Tunstall, Leandro von Werra, and Thomas Wolf, serves as a comprehensive and practical guide for data scientists and machine learning engineers on applying state-of-the-art Transformer models to real-world Natural Language Processing tasks. Centered almost entirely on the powerful Hugging Face ecosystem—a library the authors helped build—the book moves beyond theory to provide hands-on instruction for the complete model lifecycle. It meticulously walks readers through loading data, tokenization, and fine-tuning powerful pre-trained models like BERT and GPT for a wide variety of applications, including text classification, named entity recognition (NER), question answering, and text summarization. Furthermore, it addresses the critical, real-world challenges of deploying models to production, covering essential optimization techniques such as knowledge distillation and quantization to make models smaller and faster.
AIML
978-93-5542-032-9
AIML
COMPUTERS
--R-23
NATURAL LANGUAGE PROCESSING WITH TRANSFORMERS Building Language Applications with Hugging Face - SECOND EDITION - CALIFORNIA O'REILLY SPD PVT LTD 2023 - XXII 386P
NLP
"Natural Language Processing with Transformers," authored by Lewis Tunstall, Leandro von Werra, and Thomas Wolf, serves as a comprehensive and practical guide for data scientists and machine learning engineers on applying state-of-the-art Transformer models to real-world Natural Language Processing tasks. Centered almost entirely on the powerful Hugging Face ecosystem—a library the authors helped build—the book moves beyond theory to provide hands-on instruction for the complete model lifecycle. It meticulously walks readers through loading data, tokenization, and fine-tuning powerful pre-trained models like BERT and GPT for a wide variety of applications, including text classification, named entity recognition (NER), question answering, and text summarization. Furthermore, it addresses the critical, real-world challenges of deploying models to production, covering essential optimization techniques such as knowledge distillation and quantization to make models smaller and faster.
AIML
978-93-5542-032-9
AIML
COMPUTERS
--R-23