nanogpt
CommunityLearn transformers from scratch.
AuthorDoanNgocCuong
Version1.0.0
Installs0
System Documentation
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 Implementation: A clean, ~300-line Python implementation of GPT, ideal for learning.
- Reproduce GPT-2: Train and reproduce GPT-2 (124M) on datasets like OpenWebText.
- Custom Datasets: Easily train on your own text data.
- Use Case: A researcher wants to understand the inner workings of a transformer model without the complexity of large frameworks. They can use this Skill to train a small GPT model on a custom text corpus and analyze its architecture and training process.
Quick Start
Train a character-level model on Shakespeare by running python train.py config/train_shakespeare_char.py.
Dependency Matrix
Required Modules
torchtransformersdatasetstiktokenwandb
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: nanogpt Download link: https://github.com/DoanNgocCuong/continuous-training-pipeline_T3_2026/archive/main.zip#nanogpt Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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