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Small Language Models Unleashed: A Hands-On Guide to Building Efficient NLP Systems with Python, Transformers, and Quantization
Paperback
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Publisher: Independently Published
Published: Oct 29 2025
Pages: 96
Weight: 0.40
Height: 0.20 Width: 7.00 Depth: 10.00
Language: English
This book helps developers, data scientists, and AI enthusiasts create fast, resource-efficient natural language processing solutions using Python, Hugging Face Transformers, and quantization techniques. From fine-tuning models on CPUs to deploying on edge devices such as Raspberry Pi and Android, this guide covers the complete SLM lifecycle including dataset preparation, parameter-efficient fine-tuning (PEFT), model compression, and production deployment. With clear examples and real-world applications, readers learn how to build smarter, faster, and lighter AI systems without relying on massive infrastructure. What's inside: Step-by-step workflows for developing small language models in Python Techniques for parameter-efficient fine-tuning and quantization Methods for deploying models on resource-limited devices Real-world examples and cost-saving strategies About the reader:
This book is a practical blueprint for building powerful yet efficient NLP systems. Whether you want to fine-tune domain-specific models, deploy on constrained hardware, or reduce operational costs, this guide provides the tools and understanding to do so effectively.
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