Agent Skills: sparse-autoencoder-training
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.
UncategorizedID: davila7/claude-code-templates/sparse-autoencoder-training
19,6461,834
Install this agent skill to your local
Skill Files
Browse the full folder contents for sparse-autoencoder-training.
Loading file tree…
Select a file to preview its contents.