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Interpretability Toolkit

A research utility for inspecting activations, comparing model behavior, and packaging exploratory interpretability work into repeatable workflows.

Dummy project Python Internal tooling
Project facts

Snapshot

A quick summary of the project so the page feels lighter and easier to scan on both desktop and mobile.

Status Prototype
Role Design, tooling, and workflow definition
Stack Python, notebooks, local dashboards

Overview

This dummy project imagines a compact toolkit for researchers who need to inspect activations, compare runs, and capture observations without jumping between too many disconnected scripts. The goal is not just analysis, but a cleaner workflow that can survive repeated use.

Problem

Interpretability work often starts as scattered experiments. One notebook handles activations, another charts attention, and a third stores quick comparisons. Over time the process becomes difficult to reuse, and useful observations disappear into ad hoc files.

Approach

The project groups common tasks into one minimal interface: loading checkpoints, selecting layers, comparing tokens, and exporting snapshots of findings. The emphasis is not on heavy productization, but on reducing friction for recurring analysis.

Outcome

If built out further, the toolkit would shorten the path from a question to a reproducible inspection pass. It would also make it easier to share findings internally without having to hand over a fragile notebook chain every time.