datawhalechina/zero-to-sglang
Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.
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From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
Start from what inference really is, build a mini-sglang by hand, then read the real SGLang source Datawhale × RadixArk   Large models have moved on from the training race to the inference race. Once applications took off, inference cost and latency became the real bottleneck: on the same GPU, a good inference engine can serve several times more requests. Yet there are few tutorials on inference engines. They either stay at the concept level without touching code, or drop you straight into the SGLang source with no idea where to start.   This course fills that gap. The first half starts from the core questions of inference: why KV Cache exists, how prefill differs from decode, what compute-bound and memory-bound actually mean. The middle part walks you through building a mini-sglang from scratch: forward pass, generation, KV Cache, HTTP serving, Continuous Batching, Paged KV Cache, RadixAttention, added one at a time.…
Read the full README ↗ · Preview checked 2026-10-29T08:43:47.243Z
Inside the original README — Document outline
- 🎯 About
- ✨ What you will learn
- 📋 Prerequisites
- 🔗 Links
- 📖 Syllabus
- 🗓️ Writing schedule
- 🚀 Quick start
- Learning path
- Project structure
- 🤝 Contributing
- ❓ FAQ
- 💬 Reader Community
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What this repository does
Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.
Repository facts
- Owner
- datawhalechina
- Primary language
- Python
- Stars
- 1,293
- Forks
- 102
- Open issues + pull requests
- 15
- License
- Not reported — inspect the license file
- Archived
- No
- Default branch
- main
- Created
- 2026-08-27T02:24:12.000Z
- Last push
- 2026-09-20T06:34:56.000Z
Topics and intended use
Owner-supplied topics: cuda, datawhale, inference-engine, infra, kv-cache, llm, llm-inference, sglang, tutorial
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
Evaluate before installing
Review licensing and dependencies, inspect recent commits and unresolved issues, and test in an isolated environment before production use. Stars and forks alone cannot answer these questions.
Source and freshness
Source: GitHub. Metadata observed 2026-09-26T12:04:46.747Z. Daily imports are snapshots, not real-time monitoring.
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