---
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.