Abstract
Transformers have revolutionized machine learning, yet their inner workings remain opaque to many. We present TRANSFORMER EXPLAINER, an interactive visualization tool designed for non-experts to learn about Transformers through the GPT-2 model. Our tool helps users understand complex Transformer concepts by integrating a model overview and smooth transitions across abstraction levels of math operations and model structures. It runs a live GPT-2 model locally in the user's browser, empowering users to experiment with their own input and observe in real-time how the internal components and parameters of the Transformer work together to predict the next tokens. 125,000 users have used our open-source tool at https://poloclub.github.io/transformer-explainer/.
Cite
CITATION STYLE
Cho, A., Kim, G. C., Karpekov, A., Helbling, A., Wang, Z. J., Lee, S., … Chau, D. H. (2025). TRANSFORMER EXPLAINER: Interactive Learning of Text-Generative Models. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 39, pp. 29625–29627). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v39i28.35347
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