karpathy/build-nanogpt — explained in plain English
Analysis updated 2026-07-03 · repo last pushed 2024-08-13
Work through the tutorial step by step to build your own GPT-2 model and understand how language models actually work under the hood.
Train the 124M parameter model on a rented cloud GPU in about an hour for roughly $10 to see a working AI text generator you built yourself.
Use the incremental git commit structure to pause the video at any step, inspect the code changes, and resume with full context.
Experiment with the trained model by giving it prompts and observing how text generation quality improves as training progresses.
| karpathy/build-nanogpt | apple/coremltools | facebookresearch/sapiens | |
|---|---|---|---|
| Stars | 5,305 | 5,271 | 5,393 |
| Language | Python | Python | Python |
| Last pushed | 2024-08-13 | — | 2026-05-26 |
| Maintenance | Stale | — | Maintained |
| Setup difficulty | moderate | moderate | hard |
| Complexity | 3/5 | 3/5 | 4/5 |
| Audience | developer | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Full training requires a rented cloud GPU (~$10 for 1 hour), local CPU runs are possible but very slow.
A step-by-step coding tutorial that teaches you how to build and train your own GPT-2 language model from scratch, paired with a YouTube lecture and organized as incremental git commits.
Mainly Python. The stack also includes Python, PyTorch.
Stale — no commits in 1-2 years (last push 2024-08-13).
No license information is mentioned in the explanation.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly developer.
This repo across BitVibe Labs
Verify against the repo before relying on details.