Nnsight Remote Interpretability
Skill Verified ActiveProvides 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.
To enable researchers and developers to deeply inspect and modify the internal workings of PyTorch neural networks, particularly for large-scale models where local resources are a constraint, through a unified and powerful interpretability framework.
Features
- Interpret and manipulate neural network internals
- Unified API for any PyTorch architecture
- Remote execution on massive models (70B+) via NDIF
- Deferred execution and activation saving
- Gradient-based analysis
Use Cases
- Running interpretability experiments on models too large for local GPUs
- Analyzing and intervening in any PyTorch model's internal states
- Performing multi-token generation interventions and activation patching
- Sharing activations between different prompts within a single trace
Non-Goals
- Providing a consistent API across all model types (TransformerLens is preferred for this)
- Declarative, shareable interventions (pyvene is preferred for this)
- Training research components like SAEs (SAELens is preferred for this)
- Replacing local experimentation entirely when small models suffice
Trust
- info:Issues AttentionIn the last 90 days, 17 issues were opened and 4 were closed, indicating that maintainers are addressing issues but response time could be improved.
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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