nanogpt

What problem does it solve?

This Skill provides a minimalist, educational implementation of the GPT architecture, allowing users to understand and experiment with transformer models from the ground up.

Core Features & Use Cases

• Educational Transformer: Learn the inner workings of GPT with clean, concise code (~300 lines for the model, ~300 for training).
• Reproduce GPT-2: Train a GPT-2 (124M) model on OpenWebText.
• Custom Datasets: Train on your own text data, from character-level Shakespeare to large-scale datasets.
• Use Case: A researcher wants to understand how attention mechanisms work in transformers by building a small GPT model themselves, or a student wants to train a language model on a custom dataset for a class project.

Quick Start

Train a small GPT model on the Shakespeare dataset using your CPU.