Building with Small Language Models: Practical workflows for creating and deploying small language models in real-world AI projects
Product Description
Can small models really deliver big results?While large language models dominate the headlines, the future of AI is increasingly compact, efficient, and accessible. Building with Small Language Models shows how developers, engineers, and data scientists can design, fine-tune, and deploy high-performance SLMs without massive infrastructure or cloud costs.This hands-on guide takes you from core principles to advanced applications, equipping you with the knowledge and practical workflows to bring lightweight AI into real-world production. With detailed Python examples, parameter-efficient training recipes, and deployment strategies for edge and mobile devices, you’ll learn how to create AI systems that are fast, affordable, and production-ready.Whether you’re fine-tuning models with LoRA and QLoRA, compressing them with quantization and pruning, or building multilingual and multimodal assistants, this book provides the tools and insights to succeed.What You’ll Learn InsideDesign & Train Efficient Models: Understand the tradeoffs between SLMs and LLMs, and apply parameter-efficient fine-tuning methods like LoRA, QLoRA, and adapters.Optimize & Compress: Use cutting-edge techniques including GPTQ, AWQ, pruning, and distillation to shrink models without sacrificing performance.Deploy Everywhere: Export to ONNX, TensorFlow Lite, and Core ML, then run SLMs on Raspberry Pi, mobile devices, and IoT hardware.Build Smarter Agents: Integrate SLMs with LangChain, LangFlow, and agentic architectures to create autonomous, privacy-first AI assistants.Go Multilingual & Multimodal: Extend SLMs to low-resource languages, lightweight vision, and audio pipelines.Scale & Operate in Production: Implement MLOps best practices with FastAPI, TorchServe, CI/CD pipelines, and observability tools.Case Studies & Recipes: Learn from real-world deployments in healthcare, IoT, and customer support.Who This Book Is ForDevelopers and AI engineers building lightweight, resource-efficient applicationsData scientists fine-tuning domain-specific NLP systemsStartup founders and technical leaders looking to deploy AI on edge and mobile platformsAdvanced learners seeking mastery in efficient AI design and productionizationSmall language models are transforming AI by making it faster, lighter, and more accessible. From training on a laptop to deploying on constrained devices, this book is your definitive guide to creating practical, efficient AI solutions.Get your copy today and start building with small language modelsone efficient workflow at a time. Read more
