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title: SAEBase Research Lab
emoji: 🧱
colorFrom: gray
colorTo: blue
sdk: static
app_file: index.html
short_description: Explore verified SAE checkpoints, interventions and results.
tags:
- sparse-autoencoders
- mechanistic-interpretability
- research-tools
- reproducibility
- evaluation
pinned: true
---
# SAEBase Research Lab
Explore SAEBase workflows, real-checkpoint compatibility results and source-linked evaluation data in an interactive research dashboard.
Start with the **5-minute tutorial**, browse 18 model–SAE configurations and 48 verified layer sites, then inspect four recorded metrics and original per-layer reports. The dashboard displays precomputed results rather than running an LLM in the browser.
All measurements were obtained from the verified source at [`d3fd1cb1`](https://github.com/OpenSAE/SAEBase/tree/d3fd1cb1a453118611f3c7d8b44bd41d1ee7f279). Metric values may not be directly comparable across models, hooks, and evaluation protocols. Benchmark prompts use 64 held-out groups of recurring controlled templates.
**Source:** https://github.com/OpenSAE/SAEBase
**Release:** https://github.com/OpenSAE/SAEBase/releases/tag/v0.3.0
**Evaluation files:** https://github.com/OpenSAE/SAEBase/blob/main/docs/verified-model-matrix.md
The Space hosts public software demonstrations and source-linked evaluation records. Pretrained models and SAE weights remain with their original publishers.
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