nnsight-remote-interpretability
nnsight: Transparent Access to Neural Network Internals
nnsight (/ɛn.saɪt/) enables researchers to interpret and manipulate the internals of any PyTorch model, with the unique capability of running the same code locally on small models or remotely on massive models (70B+) via NDIF.
GitHub: ndif-team/nnsight (730+ stars) Paper: NNsight and NDIF: Democratizing Access to Foundation Model Internals (ICLR 2025)
Key Value Proposition
Write once, run anywhere: The same interpretability code works on GPT-2 locally or Llama-3.1-405B remotely. Just toggle remote=True.
# Local execution (small model)
with model.trace("Hello world"):
hidden = model.transformer.h[5].output[0].save()
# Remote execution (massive model) - same code!
with model.trace("Hello world", remote=True):
hidden = model.model.layers[40].output[0].save()
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