Local AI and Small Language Models

Specialize, optimize, and deploy privately
Chapters written by Guglielmo Iozzia, Pere Martra, Vivek Kalyanarangan, Keiji Kamigusa
  • October 2026
  • ISBN 9781638358862
  • 97 pages

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Choose a model that suits your task, adapt it to your needs, and build software that runs locally. This free eBook features four chapters from four Manning books, covering small language models, specialization with LoRA and DoRA, CPU inference with GGUF and llama.cpp, and application development through Ollama’s Python library. Get practical guidance on producing structured outputs, making informed quantization choices, and handling streaming responses and chatbot conversation history. Get a firmer grasp of the choices behind local AI as well as concrete techniques to try in your next project, without depending on a hosted inference service.

about the authors

Guglielmo Iozzia is a Director of AI and Applied Mathematics at Merck & Co. and a Distinguished Member of the American Society for Artificial Intelligence. He specializes in AI biomedical applications.

Pere Martra is an Applied AI Engineer, the creator of the Optipfair model efficiency library, an international AI speaker, and maintainer of widely-used LLM courses and popular open-source tools. He is the author of Large Language Models Projects.

Vivek Kalyanarangan is an AI/ML architect, researcher, and educator with over twelve years of experience designing and deploying large-scale machine learning systems.

Keiji Kamigusa is an authority in AI and machine learning with over 16 years of industry experience. A former CTO of a text mining company, he has created more than 50 courses and taught 59,000+ students. He holds three patents in text analytics and is the founder of AIGYM Inc., specializing in AI-driven corporate training.
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