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.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install nousresearch-hermes-agent-saelens
Repository
Skill path: skills/mlops/evaluation/saelens
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.
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: NousResearch.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install sparse-autoencoder-training into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/NousResearch/hermes-agent before adding sparse-autoencoder-training to shared team environments
- Use sparse-autoencoder-training for development workflows
Works across
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