Fine Tuning LLM Practical Implementation and Adaptation: Domain Specific Model Training, Optimization Strategies, and Responsible Deployment (The Applied Agentic AI Engineering Series, Band 3) - Softcover

Inhaltsangabe

While foundation models provide powerful general intelligence, real-world applications often require domain adaptation, improved consistency, and controlled outputs.
In Practical LLM Fine-Tuning and Adaptation, Zhao Colton presents a structured guide to customizing large language models for specialized tasks.
This book explores:

1. Fine-tuning fundamentals and model adaptation theory
2. Supervised fine-tuning workflows
3. Dataset preparation and curation strategies
4. Instruction tuning and alignment techniques
5. Evaluation benchmarks and quality measurement
6. Parameter-efficient fine-tuning (PEFT) methods
7. Safety and bias considerations
8. Deployment pipelines and performance monitoring

The book balances conceptual understanding with implementation strategy, helping practitioners understand not only how to fine-tune models but when it is appropriate to do so.
Readers will gain clarity on designing responsible, efficient, and maintainable model adaptation pipelines suitable for production systems.

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