All deployment variants of Gemma 3 4b It as LARQL vindexes — full, client, server, browse. • 6 items • Updated
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
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 for the full engine.
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