stanford-cs336/spring2025-lectures
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Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 1 contributor on GitHub.
Use Cases & Benefits
- Provides lecture materials and executable Python scripts for Stanford's CS336 course on language modeling from scratch.
- Enables interactive learning by allowing execution and visualization of lecture code with trace generation and frontend trace viewing.
- Use for studying foundational concepts and practical implementations of language modeling in an academic setting.
- Use for running and debugging language modeling experiments locally or on a Slurm cluster with automated trace generation.
- Use for developing or customizing a React-based frontend to visualize execution traces of language modeling algorithms.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
Watch-outs
- Warning: No commits in over a year (last push Oct 2025).
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
This repo contains the lecture materials for "Stanford CS336: Language modeling from scratch".
Located in
nonexecutable/as PDFsLocated as
lecture_*.pyin the root directorywhich generates a
var/traces/lecture_01.jsonand caches any images as appropriate.However, if you want to run it on the cluster, you can do:
which copies the files to our slurm cluster, runs it there, and copies the results back. You have to setup the appropriate environment and tweak some configs to make this work (these instructions are not complete).
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| stanford-cs336/spring2025-lectures | 1.9K | — | 6 | — |
| Category median | 56.0K | +2.3K | 29 | — |
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