# Lordog/dive-into-llms

《动手学大模型Dive into LLMs》系列编程实践教程

Repository: https://github.com/Lordog/dive-into-llms
Canonical: https://ross.abutalabs.com/products/dive-into-llms
Language: Jupyter Notebook
License Family: other
Last push: 2025-10-10T06:25:48+00:00

## Health v2 (maintenance only)
Score: 36/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 46, release rhythm 8, longevity 62
- inputs: {"age_days": 877, "days_push": 327, "days_rel": 447, "gap_med": null, "n_releases_24m": 1}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 50262, forks 6028 (observed 2026-08-28T04:12:11.779120+00:00)

## What it is
A free series of hands-on programming tutorials (in Chinese) for getting started with large language models, derived from Shanghai Jiao Tong University course materials. It covers fine-tuning and deployment, prompting and chain-of-thought, knowledge editing, math reasoning, GUI agents, alignment, and more via Jupyter notebooks.

## Use cases
- learn how to fine-tune and deploy an LLM
- get started with large language model development
- learn prompt engineering and chain-of-thought reasoning
- understand knowledge editing in language models
- build a mini R1 for math reasoning
- find a beginner LLM course with notebooks
- learn LLM alignment and safety basics

## When to choose
- you want free, beginner-friendly, hands-on LLM tutorials with runnable notebooks
- you prefer Chinese-language educational material
- you are a student building course projects or starting research on LLMs

## When to avoid
- you need production-ready code or a maintained library
- you require a permissively licensed codebase (no license is specified)
- you need English-only documentation

## Facets
- artifact type: learning-resource
- maturity: active
- function: llm-training, prompt-engineering, llm-inference, rag, machine-learning
- domain: large-language-models, tutorials, artificial-intelligence, education
- platform: python
- tags: jupyter-notebooks, hands-on-tutorial, chinese-language, fine-tuning, knowledge-editing, mathematical-reasoning, gui-agent, model-alignment, free-course

## Member repositories
- Lordog/dive-into-llms (main) score 36

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:11.779120+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:19:56.577203+00:00, confidence not recorded.
  - readme: https://github.com/Lordog/dive-into-llms (fetched 2026-08-28T04:12:11.779120+00:00, sha b659cf955432)
- Data as of 2026-08-30T08:39:29.467469+00:00.