sparse-autoencoder-training

github:zechenzhangAGI/AI-research-SKILLs · first committed 2025-12-17 · source · badge

Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.

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Listed, not yet scored. This skill has no public model test yet. It is in the scoring queue; submitted skills go first, then the most-installed.

Version history

1 commit to this file on GitHub (newest first).

2025-12-17 · commit 5b0d8bf · Add Mechanistic Interpretability category with 4 skills

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