| | 資料類型 | 狀態 | 應還日期 | 預約人數 | 館藏地 | 索書號 | 條碼號 | | 找書 | 圖書 | 在架上 | | 0 | 總館 西文圖書區  | QA76.9.N38 .I59 2026 | W116373 |
| 內容簡介 | Bigger isn't always better. Train and tune highly focused language models optimized for domain specific tasks. When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of a LLM may hurt more than it helps. Domain-Specific Small Language Models teaches you to build generative AI models optimized for specific fields. In Domain-Specific Small Language Models you'll discover: Model sizing best practices Open source libraries, frameworks, utilities and runtimes Fine-tuning techniques for custom datasets Hugging Face's libraries for SLMs Running SLMs on commodity hardware Model optimization or quantization 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. About the Technology Small-footprint language models trained on custom data sets and hosted locally can perform as well as large generalist models in speed and accuracy, often at a fraction of the cost. Domain-Specific Small Language Models shows you how to build privacy-preserving and regulation-compliant SLMs for agentic systems, specialist applications, and deployment on the edge. About the Book This is a practical book that shows you how to adapt pretrained open source models to your domain using transfer learning and parameter-efficient fine-tuning. You'll learn to minimize cost through optimization and quantization, develop secure APIs to serve your models, and deploy SLMs on commodity hardware--including small devices. The hands-on examples include integrating SLMs into RAG systems and agentic workflows. What's Inside ONNX and other quantization methods Integrate SLMs into end-to-end applications Deploy SLMs on laptops, smartphones, and other devices About the Rea | 讀者書評 | 尚無書評,
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