Transformer Explainer is an interactive visualization tool designed to help anyone learn how Transformer-based models like GPT work. It runs a live GPT-2 model right in your browser, allowing you to experiment with your own text and observe in real time how internal components and operations of the Transformer work together to predict the next tokens. Try Transformer Explainer at http://poloclub.github.io/transformer-explainer and watch a demo video on YouTube https://youtu.be/ECR4oAwocjs .
transformer-explainer.mp4 |
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| 🚀 Live Demo | 📺 Demo Video |
Transformer Explainer: Interactive Learning of Text-Generative Models. Aeree Cho, Grace C. Kim, Alexander Karpekov, Alec Helbling, Zijie J. Wang, Seongmin Lee, Benjamin Hoover, Duen Horng Chau. Poster, IEEE VIS 2024.
- Node.js v20 or higher
- NPM v10 or higher
git clone https://github.com/poloclub/transformer-explainer.git
cd transformer-explainer
npm install
npm run devThen, on your web browser, access http://localhost:5173.
Transformer Explainer was created by Aeree Cho, Grace C. Kim, Alexander Karpekov, Alec Helbling, Jay Wang, Seongmin Lee, Benjamin Hoover, and Polo Chau at the Georgia Institute of Technology.
@article{cho2024transformer,
title = {Transformer Explainer: Interactive Learning of Text-Generative Models},
shorttitle = {Transformer Explainer},
author = {Cho, Aeree and Kim, Grace C. and Karpekov, Alexander and Helbling, Alec and Wang, Zijie J. and Lee, Seongmin and Hoover, Benjamin and Chau, Duen Horng},
journal={IEEE VIS},
year={2024}
}The software is available under the MIT License.
If you have any questions, feel free to open an issue or contact Aeree Cho or any of the contributors listed above.
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