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skill
sparse-autoencoder-training
ANo problem foundgqf2008/hermez-ai
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.
sparse-autoencoder-training got grade A on our automated scan on 2026-10-21.
Details
Source
Public file: https://github.com/gqf2008/hermez-ai/blob/2637afd6693cb0ce0da5ac2ac72527b8d3f5b442/skills/mlops/saelens/SKILL.md
Last scanned: (Oct 21, 2026, 2:08 p.m. ET)
Category: uncategorized
License: Present
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Related
Run all code generation (protobuf, sqlc, frontend build)
name: ship description: Release protocol: pre-flight checks, changelog, semantic version, tag, deploy. disable-model-invocation: true
name: init description: Bootstrap the .resonance/ project memory (soul, state, docs scaffold). Run once per new project. disable-model-invocation: true
name: goal description: The autonomous goal loop: frame, decompose, then build and verify each slice against real checks, bounded, never auto-ship. disable-model-invocation: true