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.
安装
npx skills add davila7/claude-code-templates --skill sparse-autoencoder-trainingnpx skills add davila7/claude-code-templates --skill sparse-autoencoder-training -a claude-code -gnpx skills add davila7/claude-code-templates --skill sparse-autoencoder-training -a codex -ggemini skills install https://github.com/davila7/claude-code-templates.git --path cli-tool/components/skills/ai-research/mechanistic-interpretability-saelensgh skill install davila7/claude-code-templates sparse-autoencoder-traininggit clone --depth 1 https://github.com/davila7/claude-code-templates /tmp/davila7__claude-code-templates
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/davila7__claude-code-templates/cli-tool/components/skills/ai-research/mechanistic-interpretability-saelens ~/.claude/skills/sparse-autoencoder-training # Claude Code
cp -R /tmp/davila7__claude-code-templates/cli-tool/components/skills/ai-research/mechanistic-interpretability-saelens ~/.agents/skills/sparse-autoencoder-training # Codex, Cursor, Gemini CLI, Copilot, OpenCode