datawhalechina/self-llm resource

Health v2 · maintenance only

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31927 stars · 3101 forks observed · 2026-08-28

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

A Chinese-language open-source tutorial guide (Datawhale) for deploying, using, and fine-tuning open-source large language models and multimodal models on Linux. It covers environment setup, local deployment of models like Qwen, ChatGLM, LLaMA, and InternLM, plus full-parameter and LoRA fine-tuning.

Use cases

• learn to deploy open-source LLMs locally on Linux
• fine-tune an LLM with LoRA on my own data
• set up the environment for running Qwen or ChatGLM
• build a chatbot fine-tuned on custom character dialogue
• find a beginner-friendly Chinese LLM tutorial
• deploy an open-source multimodal model
• integrate a local LLM with LangChain

When to choose

• you are a Chinese-speaking beginner wanting step-by-step LLM deployment and fine-tuning guides
• you want free, low-cost local LLM usage without paid APIs
• you need tutorials covering many mainstream open-source models in one place

When to avoid

• you need production-grade deployment tooling rather than tutorials
• you work primarily on Windows or macOS without Linux access
• you want deep theoretical training-from-scratch content rather than practical usage

Facets

learning-resource · maturity active

llm-inference llm-training rag prompt-engineering large-language-models tutorials machine-learning python open-source-llm lora-fine-tuning chinese-tutorial model-deployment datawhale jupyter-notebooks multimodal-models natural-language-processing linux gpu

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markdown · JSON · MCP: product_card(name="datawhalechina/self-llm")