Transformer Explainer: Interactive Learning of Text-Generative Models (9.0k stars)
What it does
All text below is quoted directly from the project README.
>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 poloclub.github.io and watch a demo video on YouTube youtu.be.
Research Paper:
>Transformer Explainer: Learning LLM Transformers with Interactive Visual Explanation and Experimentations. Aeree Cho, Grace C. Kim, Alexander Karpekov, Seongmin Lee, Alec Helbling, Benjamin Hoover, Zijie J. Wang, Minsuk Kahng, Duen Horng Chau. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems.
How to run locally:
Prerequisites
- Node.js v20 or higher
- NPM v10 or higher
>Then, on your web browser, access localhost.
Credits:
>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.
More AI explainers to check out:
- Diffusion Explainer for learning how Stable Diffusion transforms text prompt into image
- CNN Explainer
- GAN Lab for playing with Generative Adversarial Networks in browser
Repository
poloclub/transformer-explainer
Repository stats
|Metric|Value|
|:-|:-|
|Stars|8,962|
|Forks|1.0k|
|Last release|v0.0.1 (2024-06-11)|
|Languages|JavaScript 95%, Svelte 3.8%, TypeScript 0.8%|
|Contributors|11|
|AI contributor accounts (Claude / Codex / Cursor / Copilot)|None|
|AI co-authored commits|None|
Main contributor
|Field|Value|
|:-|:-|
|Name|Aeree Cho|
|GitHub|@aereeeee|
|Commits to this repo|74 (top contributor)|
|Company / Location|Georgia Tech / Atlanta|
|Followers|135|
1 point
Mentions
Transformer Explainer: a neat visual summary poloclub/transformer-explainer
Transformer Explainer: Interactive Learning of Text-Generative Models (9.0k stars) What it does All text below is quoted directly from the project README. >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 poloclub.github.io and watch a demo video on YouTube youtu.be. Research Paper: >Transformer Explainer: Learning LLM Transformers with Interactive Visual Explanation and Experimentations. Aeree Cho, Grace C. Kim, Alexander Karpekov, Seongmin Lee, Alec Helbling, Benjamin Hoover, Zijie J. Wang, Minsuk Kahng, Duen Horng Chau. Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. How to run locally: Prerequisites - Node.js v20 or higher - NPM v10 or higher >Then, on your web browser, access localhost. Credits: >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. More AI explainers to check out: - Diffusion Explainer for learning how Stable Diffusion transforms text prompt into image - CNN Explainer - GAN Lab for playing with Generative Adversarial Networks in browser Repository poloclub/transformer-explainer Repository stats |Metric|Value| |:-|:-| |Stars|8,962| |Forks|1.0k| |Last release|v0.0.1 (2024-06-11)| |Languages|JavaScript 95%, Svelte 3.8%, TypeScript 0.8%| |Contributors|11| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|None| |AI co-authored commits|None| Main contributor |Field|Value| |:-|:-| |Name|Aeree Cho| |GitHub|@aereeeee| |Commits to this repo|74 (top contributor)| |Company / Location|Georgia Tech / Atlanta| |Followers|135|