nanoGPT

GitHub describes it as The simplest, fastest repository for training/finetuning medium-sized GPTs.. The repository metadata lists Python as its primary language. The metadata lists the MIT license. This article stays within the project description and details documented in the GitHub repository README.

GitHub describes it as The simplest, fastest repository for training/finetuning medium-sized GPTs.. The repository metadata lists Python as its primary language. The metadata lists the MIT license. The README describes the project this way: Update Nov 2025 nanoGPT has a new and improved cousin called nanochat. It is very likely you meant to use/find nanochat instead. nanoGPT (this repo) is now very old and deprecated but I will leave it up for posterity.

The README section "nanoGPT" states: The simplest, fastest repository for training/finetuning medium-sized GPTs. It is a rewrite of minGPT that prioritizes teeth over education. Still under active development, but currently the file train.py reproduces GPT-2 (124M) on OpenWebText, running on a single 8XA100 40GB node in about 4 days of training. The code itself is plain and readable: train.py is a ~300-line boilerplate training loop and model.py a ~300-line GPT model definition, which can optionally load the GPT-2 weights from OpenAI. That's it.

The README section "nanoGPT" states: Because the code is so simple, it is very easy to hack to your needs, train new models from scratch, or finetune pretrained checkpoints (e.g. biggest one currently available as a starting point would be the GPT-2 1.3B model from OpenAI).

The README section "install" states: - pytorch <3 - numpy <3 - transformers for huggingface transformers <3 (to load GPT-2 checkpoints) - datasets for huggingface datasets <3 (if you want to download + preprocess OpenWebText) - tiktoken for OpenAI's fast BPE code <3 - wandb for optional logging <3 - tqdm for progress bars <3

The repository README is the source for this review. It does not replace a local installation or an independent test.

• Source 1 · Project repository
• Source 2 · README