Domain-Specific Small Language Models

Guglielmo Iozzia (Autor)

Buch | Hardcover

300 Seiten

2026
Manning Publications (Verlag)
978-1-63343-670-1 (ISBN)

Noch nicht erschienen (ca. April 2026)
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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.

Want LLM power without the LLM price tag? Crave models that fit your data, laptop, and budget? Stop renting GPUs you cannot afford. Start building Domain-Specific Small Language Models today. Own your AI stack, end to end.

Model sizing best practices: pick the smallest architecture that still delivers top-tier accuracy.

Open-source toolchain: leverage Hugging Face, PEFT, and quantization libraries for zero-license freedom.

Fine-tuning workflows: adapt existing checkpoints to niche datasets in hours, not weeks.

Commodity hardware deployment: run chat, code, or bio models locally on a single GPU or CPU.

Retrieval-augmented generation: fuse SLMs with RAG pipelines for grounded, up-to-date answers.

Cost-control checklists: slash cloud spends and eliminate dependency on expensive foundation APIs.

Domain-Specific Small Language Models, by AI director Guglielmo Iozzia, is a field guide packed with runnable Python code and real-world engineering insight.

Step-by-step chapters demystify transformer architecture, quantization, and PEFT fine-tuning, then walk you through building RAG systems and autonomous agents that rely solely on SLMs. Clear diagrams, annotated notebooks, and troubleshooting tips keep learning smooth.

You will finish with reusable templates, deployment scripts, and the confidence to deliver performant language models under tight hardware and budget constraints.

Perfect for Python-savvy machine-learning engineers, data scientists, and technical leads who need domain-tuned AI now.

Guglielmo Iozzia is Director of ML/AI and Applied Mathematics at MSD, known for turning complex theory into deployable AI solutions. With decades of cross-industry experience, Guglielmo brings pragmatic clarity and code-first rigor to every page. He distills real-world expertise into step-by-step guidance that helps engineers ship reliable, budget-friendly language models.

PART 1: FIRST STEPS

1 LARGE LANGUAGE MODELS

PART 2: CORE DOMAIN-SPECIFIC LLMS

2 TUNING FOR A SPECIFIC DOMAIN

3 RUNNING INFERENCE

4 EXPLORING ONNX

5 QUANTIZING FOR YOUR PRODUCTION ENVIRONMENT

PART 3: REAL-WORLD USE CASES

6 GENERATING PYTHON CODE

7 GENERATING PROTEIN STRUCTURES

PART 4: ADVANCED CONCEPTS

8 ADVANCED QUANTIZATION TECHNIQUES

9 PROFILING INSIGHTS

10 DEPLOYMENT AND SERVING

11 RUNNING ON YOUR LAPTOP

12 CREATING END-TO-END LLM APPLICATIONS

13 ADVANCED COMPONENTS FOR LLM APPLICATIONS

14 TEST-TIME COMPUTE AND SMALL LANGUAGE MODELS

Erscheint lt. Verlag	6.4.2026
Verlagsort	New York
Sprache	englisch
Themenwelt	Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
	Informatik ► Software Entwicklung ► SOA / Web Services
	Informatik ► Software Entwicklung ► User Interfaces (HCI)
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Informatik ► Web / Internet
ISBN-10	1-63343-670-5 / 1633436705
ISBN-13	978-1-63343-670-1 / 9781633436701
Zustand	Neuware