Awesome
Dodrio <a href="https://poloclub.github.io/dodrio/"><img align="right" src="public/figures/dodrio-logo.svg" height="38"></img></a>
An interactive visualization system designed to help NLP researchers and practitioners analyze and compare attention weights in transformer-based models with linguistic knowledge.
<a href="https://youtu.be/qB-T9j7UTgE" target="_blank"><img src="https://i.imgur.com/wA5wudI.png" style="max-width:100%;"></a>
For more information, check out our manuscript:
Dodrio: Exploring Transformer Models with Interactive Visualization. Zijie J. Wang, Robert Turko, and Duen Horng Chau. arXiv preprint 2021. arXiv:2103.14625.
Live Demo
For a live demo, visit: http://poloclub.github.io/dodrio/
Running Locally
Clone or download this repository:
git clone git@github.com:poloclub/dodrio.git
# use degit if you don't want to download commit histories
degit poloclub/dodrio
Install the dependencies:
npm install
Then run Dodrio:
npm run dev
Navigate to localhost:5000. You should see Dodrio running in your broswer :)
To see how we trained the Transformer or customize the visualization with a different model or dataset, visit the ./data-generation/
directory.
Credits
Dodrio was created by <a href="https://zijie.wang/">Jay Wang</a>, <a href="https://www.linkedin.com/in/robert-turko/">Robert Turko</a>, and <a href="https://www.cc.gatech.edu/~dchau/">Polo Chau</a>.
Citation
@inproceedings{wangDodrioExploringTransformer2021,
title = {Dodrio: {{Exploring Transformer Models}} with {{Interactive Visualization}}},
shorttitle = {Dodrio},
booktitle = {Proceedings of the 59th {{Annual Meeting}} of the {{Association}} for {{Computational Linguistics}} and the 11th {{International Joint Conference}} on {{Natural Language Processing}}: {{System Demonstrations}}},
author = {Wang, Zijie J. and Turko, Robert and Chau, Duen Horng},
year = {2021},
pages = {132--141},
publisher = {{Association for Computational Linguistics}},
address = {{Online}},
language = {en}
}
License
The software is available under the MIT License.
Contact
If you have any questions, feel free to open an issue or contact Jay Wang.