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---
license: mit
library_name: transformers
pipeline_tag: feature-extraction
---
# SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
This repository contains models described in the paper [SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability](https://huggingface.co/papers/2503.09532). SAEBench is a comprehensive evaluation suite that measures SAE performance across seven diverse metrics, spanning interpretability, feature disentanglement and practical applications like unlearning.
* Project Page: [https://saebench.xyz](https://saebench.xyz)
* Code: [https://github.com/adamkarvonen/SAEBench](https://github.com/adamkarvonen/SAEBench) |