Hands-On Small Language Models (Practical Patterns for Building Efficient Applications with SLMs)

Large language models have reshaped what's possible in AI—but their size, cost, and complexity can make them difficult to use in real-world production. Small language models (SLMs) offer a more practical alternative: they're efficient, focused, and built for applications that demand agility, privacy, and control. Hands-On Small Language Models provides a hands-on guide to understanding, building, and deploying these compact models to power specialized agentic applications.

Author Alex Thomas, principal data scientist at John Snow Labs, draws on years of experience in natural language processing and applied AI to show how SLMs are democratizing the generative AI landscape. Through clear explanations and guided projects, including the development of a multi-functional movie chatbot, you'll learn how to combine, deploy, and monitor SLMs both locally and in the cloud.

• Build and customize multi-functional agentic chatbots using small language models
• Compare and select models for specialized AI workflows
• Integrate multiple SLMs into coordinated, intelligent applications
• Deploy, monitor, and scale applications efficiently across environments
• Understand how SLMs enable safer, more sustainable, and more cost-effective AI adoption