nnsight-remote-interpretability
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.
npx skills add Orchestra-Research/AI-Research-SKILLs --skill nnsight --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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](https://github.com/ndif-team/nnsight) (730+ stars) **Paper**: [NNsight and NDIF: Democratizing Access to Foundation Model Internals](https://arxiv.org/abs/2407.14561) (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`. ```python # 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() ``` ## When to Use nnsight **Use nnsight when you need to:** - Run interpretability experiments on models too large for local GPUs (70B, 405B) - Work with any PyTorch architecture (transformers, Mamba, custom models) - Perform multi-token generation interventions - Share a
- Key Value Proposition
- When to Use nnsight
- Installation
- Core Concepts
- LanguageModel Wrapper
- Tracing Context
- Proxy Objects
- Workflow 1: Activation Analysis
- Step-by-Step
- Checklist
- Workflow 2: Activation Patching
- Systematic Patching Sweep
- Workflow 3: Remote Execution with NDIF
- NDIF Setup
Basic installation pip install nnsight For vLLM support pip install "nnsight[vllm]"
What does the nnsight-remote-interpretability skill do?
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch architecture.
How do I install it?
Run `npx skills add Orchestra-Research/AI-Research-SKILLs --skill nnsight --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From Orchestra-Research/AI-Research-SKILLs, a repository with 11,391 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.