Large Language Models for Developers : A Prompt-based Exploration of LLMs

Language: English

Published by De Gruyter Jan 2025, 2025

1501523562 / 9781501523564

  • Softcover
  • New
See all details

Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

5-star seller

AbeBooks seller since August 14, 2006

View this seller's items
Softcover

Condition: New

£ 59.32

£ 39.05 shipping 
Ships from Germany to U.S.A.

Quantity: 1 available

Add to basket
Free 30-day returns

Item description from seller

Neuware - This book offers a thorough exploration of Large Language Models (LLMs), guiding developers through the evolving landscape of generative AI and equipping them with the skills to utilize LLMs in practical applications. Designed for developers with a foundational understanding of machine learning, this book covers essential topics such as prompt engineering techniques, fine-tuning methods, attention mechanisms, and quantization strategies to optimize and deploy LLMs. Beginning with an introduction to generative AI, the book explains distinctions between conversational AI and generative models like GPT-4 and BERT, laying the groundwork for prompt engineering (Chapters 2 and 3). Some of the LLMs that are used for generating completions to prompts include Llama-3.1 405B, Llama 3, GPT-4o, Claude 3, Google Gemini, and Meta AI. Readers learn the art of creating effective prompts, covering advanced methods like Chain of Thought (CoT) and Tree of Thought prompts. As the book progresses, it details fine-tuning techniques (Chapters 5 and 6), demonstrating how to customize LLMs for specific tasks through methods like LoRA and QLoRA, and includes Python code samples for hands-on learning. Readers are also introduced to the transformer architecture's attention mechanism (Chapter 8), with step-by-step guidance on implementing self-attention layers. For developers aiming to optimize LLM performance, the book concludes with quantization techniques (Chapters 9 and 10), exploring strategies like dynamic quantization and probabilistic quantization, which help reduce model size without sacrificing performance.FEATURES- Covers the full lifecycle of working with LLMs, from model selection to deployment- Includes code samples using practical Python code for implementing prompt engineering, fine-tuning, and quantization- Teaches readers to enhance model efficiency with advanced optimization techniques- Includes companion files with code and images -- available from the publisher.…

Seller Inventory # 9781501523564

Title
Large Language Models for Developers : A Prompt-based Exploration of LLMs
Author
Oswald Campesato
Publisher
De Gruyter Jan 2025
Publication year
2025
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1501523562
ISBN 13
9781501523564
Item weight
1,479 grams
Dimensions
229x152x56 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item7 to 10 business days5 to 7 business days
First item£ 39.05£ 54.03
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.

Payment methods

  • Visa
  • Mastercard
  • American Express
  • Apple Pay
  • Google Pay
  • Bank Wire Transfer
  • Check
  • Paypal

Store description

Das Unternehmen AHA-BUCH GmbH: Seit der Gründung von AHA-BUCH im Juli 2005 ist unser Hauptziel, zufriedenen Kunden so schnell und so preisgünstig wie möglich ihren Bücherwunsch zu erfüllen. Unsere Firma beschäftigt 16 Mitarbeiter, die nur ein Ziel kennen: den Kunden und seine Wünsche! Auf über 3700 m2 Fläche haben wir über 100.000 Bücher, Modernes Antiquariat und Spiele auf Lager.

Specialty

Kinderbücher & Kinderhör Casetten, German Books, Software, Natur & Tiere, Ratgeber, Sachbücher, Englische Bücher, Medizin & Gesundheit, Universität & Studium

Seller's business information

AHA-BUCH GmbH

Garlebsen 48
Einbeck, Germany 37574