Shypd.aiThe largest open index of AI toolsLLM-Engineers-Handbook is an Open Source research and education tool that provides a practical guide for building end-to-end LLM-based systems. It covers data collection, LLM training pipelines, RAG systems, and AWS deployment using LLMOps best practices.
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The LLM-Engineers-Handbook is an official repository and practical guide for building end-to-end LLM-based systems, developed by Paul Iusztin and Maxime Labonne. It covers essential aspects from data collection and generation to LLM training pipelines, simple RAG systems, and production-ready AWS deployment. The handbook emphasizes LLMOps best practices, including comprehensive monitoring, testing, and evaluation frameworks. It details the use of various tools and cloud services like HuggingFace, Comet ML, Opik, ZenML, AWS, MongoDB, Qdrant, and GitHub Actions. The repository provides actively maintained code, installation instructions, and guidance on setting up local development and cloud deployment environments.
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