# modelscope/modelscope-classroom

Repository: https://github.com/modelscope/modelscope-classroom
Canonical: https://ross.abutalabs.com/products/modelscope-classroom
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Last push: 2026-04-27T09:27:20+00:00

## Health v2 (maintenance only)
Score: 61/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 79, release rhythm 35, longevity 65
- inputs: {"age_days": 914, "days_push": 128, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1482, forks 180 (observed 2026-08-28T04:04:51.062628+00:00)

## What it is
ModelScope Classroom is a collection of deep learning and large language model tutorials from the ModelScope community, delivered as Jupyter notebooks, markdown lessons, and technical blogs. It covers the full LLM lifecycle including training, inference, deployment, RLHF, agents, and AIGC (text-to-image/video) with hands-on examples.

## Use cases
- learn how to fine-tune large language models
- tutorials for deploying LLMs with vLLM or llama.cpp
- learn RAG and agent development with hands-on notebooks
- understand diffusion models and text-to-image generation
- study RLHF techniques like PPO and GRPO
- beginner deep learning course with practical exercises
- find technical surveys on LLM research topics

## When to choose
- you want structured, notebook-based tutorials for LLM training and deployment
- you prefer learning with runnable examples using tools like LLaMA-Factory, unsloth, and vLLM
- you want Chinese-language deep learning and AIGC course material
- you need curated technical surveys and daily paper digests

## When to avoid
- you need production-ready software rather than educational content
- you require English-only documentation
- you want a maintained library with an API rather than tutorials

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, llm-training, llm-inference, rag, agent-framework, stable-diffusion
- domain: tutorials, large-language-models, deep-learning, artificial-intelligence, machine-learning
- platform: python, cross-platform
- tags: jupyter-notebooks, llm-tutorial, aigc, modelscope, chinese-language, course-materials

## Member repositories
- modelscope/modelscope-classroom (main) score 61

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:51.062628+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 2026-08-30T04:34:08.075327+00:00, confidence not recorded.
  - readme: https://github.com/modelscope/modelscope-classroom (fetched 2026-08-28T04:04:51.062628+00:00, sha 6681e413d58f)
- Data as of 2026-08-30T08:39:29.467469+00:00.