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.
$npx -y skills add mustafakemal0146/fetih --skill saelensInstalls into the current project.
Run `npx skills use "https://github.com/mustafakemal0146/fetih" --skill "mustafakemal0146/fetih/saelens"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/mustafakemal0146/fetih" that are relevant to the current task. Run `npx skills add "https://github.com/mustafakemal0146/fetih"` and select the relevant skills, then follow their instructions.