Hoper-J/AI-Guide-and-Demos-zh_CN resource
这是一份入门AI/LLM大模型的逐步指南，包含教程和演示代码，带你从API走进本地大模型部署和微调，代码文件会提供Kaggle或Colab在线版本，即便没有显卡也可以进行学习。项目中还开设了一个小型的代码游乐场🎡，你可以尝试在里面实验一些有意思的AI脚本。同时，包含李宏毅 (HUNG-YI LEE）2024生成式人工智能导论课程的完整中文镜像作业。 observed · 2026-08-28
Health v2 · maintenance only
66/100
- Activity 97
- Release rhythm 35
- Longevity 51
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 722
- days_rel: n/a
- days_push: 19
- n_releases_24m: 0
Adoption not part of the score
4465 stars · 472 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A Chinese-language step-by-step guide and demo code collection for getting started with AI and LLMs, covering API usage, local model deployment, fine-tuning, AI image generation, and MCP, with Kaggle/Colab online versions of all code. It also mirrors the assignments of Hung-Yi Lee's 2024 Generative AI course and includes a small code playground.
Use cases
- learn how to call LLM APIs with the OpenAI SDK
- get started with large language models as a beginner
- fine-tune an LLM without owning a GPU
- learn Stable Diffusion text-to-image generation
- follow Hung-Yi Lee's 2024 generative AI course assignments in Chinese
- run AI demo scripts in Colab or Kaggle for free
- understand MCP and FastMCP basics
- set up a deep learning environment with Docker or uv
When to choose
- you are a Chinese-speaking beginner entering AI/LLM development
- you lack a local GPU and need free cloud notebooks
- you want guided, hands-on demos rather than theory-only videos
- you want structured assignments accompanying a university generative AI course
When to avoid
- you need production-grade code or a maintained library to depend on
- you need English-language materials
- you are already an advanced practitioner seeking cutting-edge research content
- you need comprehensive coverage of a single topic rather than a broad intro
Facets
learning-resource · maturity active
llm-inference llm-training rag stable-diffusion mcp sdk artificial-intelligence large-language-models deep-learning tutorials python cross-platform chinese-language tutorial colab kaggle openai-sdk fine-tuning hung-yi-lee-course code-playground beginner-friendly natural-language-processing web-server
1 source
- readme: https://github.com/Hoper-J/AI-Guide-and-Demos-zh_CN · fetched 2026-08-28 · e123b81bcb5e
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Hoper-J/AI-Guide-and-Demos-zh_CN | main | 66 |
For agents
markdown · JSON · MCP: product_card(name="Hoper-J/AI-Guide-and-Demos-zh_CN")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem