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 ## Overview
 Graphbook is a framework for building efficient, visual DAG-structured ML workflows composed of nodes written in Python. Graphbook provides common ML processing features such as multiprocessing IO and automatic batching, and it features a web-based UI to assemble, monitor, and execute data processing workflows. It can be used to prepare training data for custom ML models, experiment with custom trained or off-the-shelf models, and to build ML-based ETL applications. Custom nodes can be built in Python, and Graphbook will behave like a framework and call lifecycle methods on those nodes.
 
+<p align="center">
+  <a href="https://graphbook.ai">
+    <img src="https://media.githubusercontent.com/media/rsamf/public/main/docs/overview/huggingface-pipeline-demo.gif" alt="Huggingface Pipeline Demo" width="512">
+  </a>
+  <div align="center">Build, run, monitor!</div>
+</p>
+
 ## Status
 Graphbook is in a very early stage of development, so expect minor bugs and rapid design changes through the coming releases. If you would like to [report a bug](https://github.com/graphbookai/graphbook/issues/new?template=bug_report.md&labels=bug) or [request a feature](https://github.com/graphbookai/graphbook/issues/new?template=feature_request.md&labels=enhancement), please feel free to do so. We aim to make Graphbook serve our users in the best way possible.