CircuitKit

Discover, evaluate, and intervene on circuits in transformer models.
One call takes a model + task to a discovered circuit, a 6-pillar faithfulness score, and a intervened HuggingFace checkpoint.

CircuitKit is a framework for mechanistic interpretability. Given a model and a task, it discovers the circuit driving that behaviour, evaluates how faithful it is, and lets you act on it (prune, quantize, edit, steer, or fine-tune), then export a reloadable HuggingFace checkpoint.

No GPU required for the quickstart — GPT-2 runs on CPU in a few minutes.

Quick start

# CPU-only, no GPU needed:
pip install -e .

# For benchmarking, add: pip install -e ".[benchmarks]"

from circuitkit import Pipeline

pipe = Pipeline("gpt2", task="ioi")
pipe.discover(algorithm="eap-ig", sparsity=0.3)
pipe.evaluate()
pipe.prune()
pipe.export("./checkpoint")

Also works as a CLI and YAML config.

What is a circuit?

A circuit is the minimal set of attention heads and MLP layers in a transformer that drives a specific behaviour. Most interp tooling stops at "here is a subgraph with attribution scores." CircuitKit goes further: it prunes (or quantizes) the model down to that subgraph, exports a reloadable HuggingFace checkpoint, and measures how faithful the pruned model stays. Because the circuit is task-specific, this produces a task-specialized checkpoint — not a general-purpose compressed model.

What you can do

Why CircuitKit?

Next steps

Tests

pip install -e ".[dev]"
pytest tests/ -q

Citation

@software{circuitkit2026,
  title  = {CircuitKit: Circuit Discovery, Evaluation, and Application Toolkit
            for Mechanistic Interpretability},
  author = {Seth, Pratinav and Gosalia, Hem and Kasliwal, Aditya
            and Sankarapu, Vinay Kumar},
  year   = {2026},
  version = {1.0.0},
  url    = {https://github.com/Lexsi-Labs/CircuitKIT}
}

License

Lexsi Labs Source Available License (LSAL) v1.1: free for research, evaluation, education, and audit; commercial use requires a separate license; responsible-use conditions apply. See LICENSE.md.