Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Enhancing LLM Performance: Efficacy, Fine-Tuning, and Inference Techniques

Enhancing LLM Performance: Efficacy, Fine-Tuning, and Inference Techniques

Way, Andy
Rezagholizadeh, Mehdi
Passban, Peyman

Hardcover

Series: Machine Translation: Technologies and Applications, Book 7

General ComputersProbability & Statistics

Currently unavailable to order

ISBN10: 3031857461
ISBN13: 9783031857461
Publisher: Springer
Published: Jul 5 2025
Pages: 183
Weight: 1.00
Height: 0.70 Width: 6.10 Depth: 8.90
Language: English
This book is a pioneering exploration of the state-of-the-art techniques that drive large language models (LLMs) toward greater efficiency and scalability. Edited by three distinguished experts--Peyman Passban, Mehdi Rezagholizadeh, and Andy Way--this book presents practical solutions to the growing challenges of training and deploying these massive models. With their combined experience across academia, research, and industry, the authors provide insights into the tools and strategies required to improve LLM performance while reducing computational demands.

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