luhengshiwo/LLMForEverybody resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

7213 stars · 671 forks observed · 2026-08-28

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

A curated collection of LLM learning materials including interview question banks, systematic paper walkthroughs (Transformer, GPT, BERT, etc.), and links to practical courses on AI Agents, RAG, and LLM application development. Content is primarily in Chinese with Jupyter Notebook materials and companion video tutorials.

Use cases

• prepare for LLM engineer job interviews
• learn how transformers and GPT models work
• study key AI papers from 2017 onward
• understand RAG and agent concepts for interviews
• find structured LLM learning roadmap
• review common large language model interview questions

When to choose

• you are preparing for LLM-related job interviews, especially with Chinese-language content
• you want a guided, chronological path through foundational LLM papers
• you prefer free curated notes plus optional paid structured courses

When to avoid

• you need production code or a software library to integrate into your project
• you require English-only learning materials
• you want hands-on model training or fine-tuning tooling rather than conceptual study

Facets

learning-resource · maturity active

llm-inference rag agent-framework prompt-engineering machine-learning large-language-models tutorials education artificial-intelligence python interview-preparation llm jupyter-notebooks chinese-content paper-reading question-bank learnllm retrieval-augmented-generation ai-agents web

Member repositories

For agents

markdown · JSON · MCP: product_card(name="luhengshiwo/LLMForEverybody")