Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).
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Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).
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model-architecture-nanogpt.SKILL.md
---name: nanogpt
description: Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Model Architecture, NanoGPT, GPT-2, Educational, Andrej Karpathy, Transformer, Minimalist, From Scratch, Training]
dependencies: [torch, transformers, datasets, tiktoken, wandb]
---# nanoGPT - Minimalist GPT Training
## Quick start
nanoGPT is a simplified GPT implementation designed for learning and experimentation.
**Installation**:
```bash
pip install torch numpy transformers datasets tiktoken wandb tqdm
```
**Train on Shakespeare** (CPU-friendly):
```bash
# Prepare data
python data/shakespeare_char/prepare.py
# Train (5 minutes on CPU)
python train.py config/train_shakespeare_char.py
# Generate text
python sample.py --out_dir=out-shakespeare-char
**Model architecture**: See [references/architecture.md](references/architecture.md) for GPT block structure, multi-head attention, and MLP layers explained simply.
**Training loop**: See [references/training.md](references/training.md) for learning rate schedule, gradient accumulation, and distributed data parallel setup.
**Data preparation**: See [references/data.md](references/data.md) for tokenization strategies (character-level vs BPE) and binary format details.
