datawhalechina/happy-llm vs labmlai/annotated_deep_learning_paper_implementations
Compare datawhalechina/happy-llm and labmlai/annotated_deep_learning_paper_implementations using the current verified snapshot: positioning, license, deployment, use cases, limitations, and original sources.
datawhalechina/happy-llm
A free, open-source Chinese-language tutorial that teaches large language model principles by guiding learners through building a LLaMA2 model from scratch in PyTorch. It covers architecture, pre-training, fine-tuning, and applications, requiring users to write and execute Python code rather than providing a ready-to-use API service.
- License
- License pending
- Deployment
- Refer to project documentation
- Use cases
- Learning & Education
- Updated
- 2026-07-17T09:29:36Z
labmlai/annotated_deep_learning_paper_implementations
A collection of simple PyTorch implementations of neural networks and related algorithms documented with explanations and rendered as side-by-side formatted notes. It is designed to help users understand deep learning algorithms better through annotated code.
- License
- MIT
- Deployment
- Refer to project documentation
- Use cases
- Learning & Education
- Updated
- 2026-07-17T05:24:41Z
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