LLM Transformers: A Practical Guide with Code, Tutorials, and Exercises

Vemula, Anand

  • 出版商: Independently Published
  • 出版日期: 2024-06-06
  • 售價: $1,320
  • 貴賓價: 9.5$1,254
  • 語言: 英文
  • 頁數: 144
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9798327728561
  • ISBN-13: 9798327728561
  • 相關分類: LangChain
  • 海外代購書籍(需單獨結帳)

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商品描述

"LLM Transformers: A Practical Guide with Code, Tutorials, and Exercises" is your comprehensive companion to mastering Large Language Models (LLMs) and Transformers. This hands-on guide equips you with the knowledge and practical skills needed to understand, build, train, deploy, and maintain state-of-the-art language models.

Starting with an introduction to the fundamentals of LLMs and Transformers, this book takes you on a journey through model training, fine-tuning, deployment strategies, and monitoring techniques. You'll explore popular frameworks such as TensorFlow, Keras, and PyTorch, learning how to implement and fine-tune LLMs for various natural language processing tasks.

Each chapter is packed with code examples, step-by-step tutorials, and exercises designed to reinforce your learning and deepen your understanding. Whether you're a beginner looking to dive into the world of LLMs or an experienced practitioner seeking to enhance your skills, this book has something for everyone.

By the end of "LLM Transformers: A Practical Guide with Code, Tutorials, and Exercises," you'll be equipped with the tools and knowledge needed to harness the power of LLMs and Transformers for your own projects, from chatbots and text summarization to question answering systems and beyond.

商品描述(中文翻譯)

《LLM Transformers: 實用指南與程式碼、教程及練習》是您掌握大型語言模型(LLMs)和 Transformers 的全面夥伴。這本實用指南為您提供了理解、構建、訓練、部署和維護最先進語言模型所需的知識和實踐技能。

本書從 LLMs 和 Transformers 的基本概念入手,帶您踏上模型訓練、微調、部署策略和監控技術的旅程。您將探索流行的框架,如 TensorFlow、Keras 和 PyTorch,學習如何為各種自然語言處理任務實現和微調 LLMs。

每一章都充滿了程式碼範例、逐步教程和設計用來加強學習和深化理解的練習。無論您是想進入 LLMs 世界的初學者,還是希望提升技能的經驗豐富的從業者,這本書都能滿足每個人的需求。

在《LLM Transformers: 實用指南與程式碼、教程及練習》的結尾,您將具備利用 LLMs 和 Transformers 的力量來實現自己的專案所需的工具和知識,從聊天機器人和文本摘要到問答系統及其他應用。