SylphAI-Inc/LLM-engineer-handbook resource

Health v2 · maintenance only

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Adoption not part of the score

5023 stars · 713 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A curated list of Large Language Model resources covering the full LLM lifecycle: pretraining, fine-tuning, serving, prompt management, and building LLM applications. It aggregates libraries, frameworks, tutorials, books, and community resources to help engineers build production-grade LLM systems.

Use cases

• find frameworks for fine-tuning large language models
• learn how to serve LLMs in production
• discover RAG and agent libraries
• find tutorials on prompt optimization
• learn the LLM engineering lifecycle end to end
• find LLMOps and evaluation tools
• locate datasets and benchmarks for LLM training

When to choose

• you are an engineer navigating the LLM tooling ecosystem
• you want a curated starting point for learning LLM engineering
• you need to compare frameworks for training, serving, or building LLM apps

When to avoid

• you need runnable software rather than a resource list
• you want deep original documentation on a single tool

Facets

learning-resource · maturity active

llm-training llm-inference rag prompt-engineering agent-framework large-language-models artificial-intelligence machine-learning tutorials awesome-lists cross-platform curated-list llm fine-tuning llmops model-serving handbook

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For agents

markdown · JSON · MCP: product_card(name="SylphAI-Inc/LLM-engineer-handbook")