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---
license: apache-2.0
tags:
- vindex
- mechanistic-interpretability
- larql
- knowledge-graph
- gemma
---
# Gemma 3 4B IT — Vindex (f16)
FFN knowledge index extracted from `google/gemma-3-4b-it` using LARQL.
Treats transformer FFN weights as a queryable knowledge graph — retrieval via dot-product graph walks against gate vectors, no matrix multiplication.
## Usage
```sql
larql> USE "hf://chrishayuk/gemma-3-4b-it-vindex";
larql> DESCRIBE "France";
```
## Contents
- 34 layers, 348.2K features
- Gate vectors, embeddings, down features/weights
- Attention weights, norms, tokenizer
- Probe-confirmed feature labels
- f16 precision
## What is a vindex?
A vindex decouples a model's knowledge from its inference machinery. The FFN weights become a queryable graph — DESCRIBE returns typed knowledge edges, WALK traces activation paths, INFER runs graph-walk inference at 31 tok/sec on CPU.
See [LARQL](https://github.com/chrishayuk/larql) for the full engine.