Summary of Penzai + Treescope: a Toolkit For Interpreting, Visualizing, and Editing Models As Data, by Daniel D. Johnson
Penzai + Treescope: A Toolkit for Interpreting, Visualizing, and Editing Models As Data
by Daniel D. Johnson
First submitted to arxiv on: 1 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces two novel tools for machine learning: Penzai, a neural network library that simplifies model manipulation by representing models as simple data structures, and Treescope, an interactive pretty-printer and array visualizer. Penzai allows users to build models using declarative combinators that expose the forward pass in the structure of the model object itself, with named axes for semantic meaning. The tree-editing selector system enables users to insert, replace, and edit model components, receiving immediate feedback through visualization with Treescope. This treatment of models as data enables various analyses and interventions without requiring explicit hooks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Penzai and Treescope are new tools that help people work with artificial intelligence (AI) models. Penzai lets you build AI models using simple instructions and shows you what’s happening inside the model. Treescope is a tool that makes it easy to see how the model works by visualizing its inputs, outputs, and structure. With these tools, you can modify and analyze AI models in ways that were previously difficult or impossible. |
Keywords
» Artificial intelligence » Machine learning » Neural network
