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Provides a comprehensive set of patterns and tools for deploying Large Language Models (LLMs) to production environments, focusing on performance optimization and scalability. It includes ready-to-use configurations for industry-standard inference servers like vLLM and HuggingFace TGI, local development setups with Ollama, and containerized deployment blueprints for Docker and Kubernetes. With built-in support for quantization techniques and monitoring instrumentation, this skill empowers engineers to transition AI models from development to high-performance, production-ready inference services efficiently.
