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mechinterp-decoder

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Reveal what features output, not just activate.

Data & Analytics#weights#analyze#decoder#SAE#feature-influence#decoder-similarity
Authorcesaregarza
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill helps researchers interpret what a given SAE decoder feature actually promotes, by analyzing the decoder weights rather than only activation patterns. It shifts focus from activation hotspots to downstream output tendencies.

Core Features & Use Cases

  • Output Influence: identify tokens the feature tends to promote or suppress.
  • Decoder Similarity: cluster features by similar output patterns to discover shared roles.
  • Experiment Workflow: integrate with mechinterp investigation to guide hypothesis formation and labeling.

Quick Start

Install dependencies for the mechinterp tooling and run the decoder CLI to view output influence:

  • Basic query: poetry run python -m splatnlp.mechinterp.cli.decoder_cli output-influence --feature-id 13934 --model ultra
  • JSON output: poetry run python -m splatnlp.mechinterp.cli.decoder_cli output-influence --feature-id 13934 --model ultra --format json
  • Explore similar features: poetry run python -m splatnlp.mechinterp.cli.decoder_cli similar --feature-id 13934 --model ultra --top-k 10

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: mechinterp-decoder
Download link: https://github.com/cesaregarza/SplatNLP/archive/main.zip#mechinterp-decoder

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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