Nnsight Remote Interpretability

This gives Claude the ability to help with nnsight, a PyTorch interpretability library that lets you access and modify neural network internals with the same code running locally on GPT-2 or remotely on 70B+ models via NDIF. The write-once-run-anywhere pattern is genuinely useful if you're prototyping interventions on small models before scaling up. It works with any PyTorch architecture, not just transformers, and handles multi-token generation interventions cleanly. The remote execution through NDIF is the main differentiator here, letting you run activation patching experiments on massive models without GPU access. If you only work with small models locally, TransformerLens is probably simpler, but for researchers who need to scale interpretability work to frontier models, this is purpose-built for that.