openai/automated-interpretability

Health v2 · maintenance only

Flags: no_releases archived no_license

Adoption not part of the score

1081 stars · 130 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenAI's code and tools for automatically generating, simulating, and scoring explanations of neuron behavior in language models, based on the 'Language models can explain neurons' paper. It also includes a neuron activation viewer and public datasets of GPT-2 XL neuron activations and explanations.

Use cases

• automatically explain what individual neurons in a language model do
• generate and score explanations of neuron behavior using LLMs
• visualize neuron activations and their explanations
• analyze GPT-2 XL neuron activation datasets
• research mechanistic interpretability of transformer models
• simulate neuron behavior to validate generated explanations

When to choose

• you want to interpret or explain neuron behavior inside large language models
• you need OpenAI's official tooling for neuron-level interpretability research
• you want to explore the released GPT-2 XL neuron activation and explanation datasets
• you are replicating or extending the neuron-explanation methodology from the paper

When to avoid

• you need a production-ready, actively maintained library with support guarantees
• you want general-purpose model explainability for classifiers rather than LLM neurons
• you cannot access Azure blob storage for the public datasets
• you need interpretability tooling for non-Python stacks

Facets

library · maturity maintenance

machine-learning nlp llm-inference data-visualization developer-tools machine-learning deep-learning large-language-models artificial-intelligence developer-tools python interpretability neuron-explanations mechanistic-interpretability gpt-2 explainability research

Member repositories

For agents

markdown · JSON · MCP: product_card(name="openai/automated-interpretability")