--- 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.