Domain-Specific Small Language Models you own this product

Guglielmo Iozzia
  • MEAP began April 2025
  • Publication in Fall 2025 (estimated)
  • ISBN 9781633436701
  • 300 pages (estimated)
  • printed in black & white

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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. 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.

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choose your plan

team

monthly
annual
$49.99
$399.99
only $33.33 per month
  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Domain-Specific Small Language Models ebook for free