Small Language NLP for Developers: Step-by-Step Techniques for Tiny Transformers, Fast Inference, and Agentic AI Pipelines (Small Language AI Series, Band 1) - Softcover

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Are you tired of sluggish AI models that rely on the cloud and heavy GPUs? Small Language NLP for Developers is your hands-on guide to building lightweight, low-latency NLP models that run efficiently on your laptop, Raspberry Pi, or mobile device.
Inside, Aaron Blake walks you step-by-step through:

• Quantization & Benchmarking: Deploy 8-bit and 4-bit models for sub-100ms inference
• Model Compression: Use structured/unstructured pruning and LoRA/QLoRA adapters
• On-Device Deployment: Docker, Python pipelines, and CPU-only setups
• LangChain & llama-cpp-python Integration: Build agentic workflows and conversational pipelines
• CI/CD Automation: Convert, test, and release production-ready models

Each chapter delivers real-world examples and ready-to-run code, guiding you from environment setup to fully functioning NLP pipelines.
Transform your AI projects with fast, efficient, and private NLP models—no cloud required.
Perfect for developers, ML engineers, and AI enthusiasts looking to run powerful AI locally.

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