LLMForEverybody

Why we included this project

This is a Chinese-language hub for getting into large language models without drowning in scattered resources. It pairs a curated interview question bank that tracks the topics hiring cycles tend to probe with a paper-reading path starting at the 2017 Transformer and moving forward through the field's milestones. Practical courses cover Agent development, RAG pipelines, and fine-tuning with common toolchains like LangChain, LlamaIndex, and Dify. Job hunters can treat the questions as a focused revision checklist, while self-taught developers get a sensible sequence to follow instead of hopping between random arxiv links. Companion video tutorials and a supporting site round it out, so you can skim the curated material and then dig into whichever toolchain or paper matches the problem you are working on today.