National Deep Inference Fabric
Official@ndif-team · United States of America
The National Deep Inference Fabric is a proposed research computing project that will enable us to crack open the mysteries inside large-scale AI
Agent Skills by National Deep Inference Fabric
Showing 6 vetted skills indexed across 1 GitHub repositories.
ndif-teamattribution-patching
Compute gradient-based attributions to approximate activation patching for circuit analysis.
ndif-teamlogit-lens
Decode layer activations into per-layer vocabulary predictions for Transformer interpretability.
ndif-teamnnsight-basics
Inspect and modify neural network activations during forward passes.
ndif-teammodel-steering
Apply steering vectors and persistent edits to transformer activations during generation.
ndif-teamactivation-patching
Patch transformer activations across layers, heads, and positions to identify causal components.
ndif-teamcausal-tracing
Compute total, direct, and indirect causal effects in transformer models.
Frequently Asked Questions About National Deep Inference Fabric
FAQPage SchemaWhat specific research tasks does the National Deep Inference Fabric enable?▼
The fabric enables granular inspection and manipulation of neural network internals, including computing gradient-based attributions, performing causal tracing to isolate model components, and applying steering vectors to modify generation behavior during forward passes.
Which technical personas benefit from these interpretability capabilities?▼
These capabilities are designed for research scientists, interpretability engineers, and machine learning practitioners focused on mechanistic transparency, circuit analysis, and the causal verification of transformer-based neural architectures.
What are the primary prerequisites for implementing these interpretability methods?▼
Implementation requires access to transformer-based model weights and a compatible environment capable of executing forward passes with hook-based activation modification. Users must have familiarity with neural network tensor operations and the specific causal analysis frameworks provided by the fabric.