- Home
- Computers
- Programming Languages
- Domain-Specific Small Language Models (Efficient AI for local deployment)
Domain-Specific Small Language Models (Efficient AI for local deployment)
List Price:
$59.99
| Expected release date is May 26th 2026 |
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Author:
Guglielmo Iozzia
Format:
Paperback
Pages:
347
Publisher:
Manning (May 26, 2026)
Imprint:
Manning
Release Date:
May 26, 2026
Language:
English
ISBN-13:
9781633436701
ISBN-10:
1633436705
Weight:
12.67oz
Dimensions:
7.375" x 9.25"
File:
Eloquence-SimonSchuster_04302026_P10025342_onix30-20260430.xml
List Price:
$59.99
Pub Discount:
37
As low as:
$46.19
Publisher Identifier:
P-SS
Discount Code:
A
Folder:
Eloquence
Overview
Bigger isn’t always better. Train and tune highly focused language models optimized for domain specific tasks.
When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of a LLM may hurt more than it helps. Domain-Specific Small Language Models teaches you to build generative AI models optimized for specific fields.
In Domain-Specific Small Language Models you’ll discover:
• Model sizing best practices
• Open source libraries, frameworks, utilities and runtimes
• Fine-tuning techniques for custom datasets
• Hugging Face’s libraries for SLMs
• Running SLMs on commodity hardware
• Model optimization or quantization
Perfect for cost- or hardware-constrained environments, Small Language Models (SLMs) train on domain specific data for high-quality results in specific tasks. In Domain-Specific Small Language Models you’ll develop SLMs that can generate everything from Python code to protein structures and antibody sequences—all on commodity hardware.
About the book
Domain-Specific Small Language Models teaches you how to create language models that deliver the power of LLMs for specific areas of knowledge. It provides a practical, application-focused counterpart to foundational texts like Sebastian Raschka’s Build a Large Language Model (From Scratch), showing you how to adapt large-scale concepts for efficient, specialized use. You’ll learn to minimize the computational horsepower your models require, while keeping high–quality performance times and output. You’ll appreciate the clear explanations of complex technical concepts alongside working code samples you can run and replicate on your laptop. Plus, you’ll learn to develop and deliver RAG systems and AI agents that rely solely on SLMs, and without the costs of foundation model access.
About the reader
For machine learning engineers familiar with Python.
About the author
Guglielmo Iozzia is a Director, ML/AI and Applied Mathematics at MSD. He studied Electronic and Biomedical Engineering at the University of Bologna, has an extensive background in Software and ML/AI Engineering applied to real-life use cases across different industries, such as Biotech Manufacturing, Healthcare, Cloud Operations, and Cyber Security.
Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of a LLM may hurt more than it helps. Domain-Specific Small Language Models teaches you to build generative AI models optimized for specific fields.
In Domain-Specific Small Language Models you’ll discover:
• Model sizing best practices
• Open source libraries, frameworks, utilities and runtimes
• Fine-tuning techniques for custom datasets
• Hugging Face’s libraries for SLMs
• Running SLMs on commodity hardware
• Model optimization or quantization
Perfect for cost- or hardware-constrained environments, Small Language Models (SLMs) train on domain specific data for high-quality results in specific tasks. In Domain-Specific Small Language Models you’ll develop SLMs that can generate everything from Python code to protein structures and antibody sequences—all on commodity hardware.
About the book
Domain-Specific Small Language Models teaches you how to create language models that deliver the power of LLMs for specific areas of knowledge. It provides a practical, application-focused counterpart to foundational texts like Sebastian Raschka’s Build a Large Language Model (From Scratch), showing you how to adapt large-scale concepts for efficient, specialized use. You’ll learn to minimize the computational horsepower your models require, while keeping high–quality performance times and output. You’ll appreciate the clear explanations of complex technical concepts alongside working code samples you can run and replicate on your laptop. Plus, you’ll learn to develop and deliver RAG systems and AI agents that rely solely on SLMs, and without the costs of foundation model access.
About the reader
For machine learning engineers familiar with Python.
About the author
Guglielmo Iozzia is a Director, ML/AI and Applied Mathematics at MSD. He studied Electronic and Biomedical Engineering at the University of Bologna, has an extensive background in Software and ML/AI Engineering applied to real-life use cases across different industries, such as Biotech Manufacturing, Healthcare, Cloud Operations, and Cyber Security.
Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.
