ModelFarm · arnold-1.5b-engram-evoked

Steering-vector (engram) persona package on Qwen/Qwen2.5-1.5B-Instruct, produced by the Arnold Persona Lab persona-stack harness. Persona: Arnold Schwarzenegger.

What this is

A difference-in-means steering vector (persona engram) read from the persona corpus and injected into the residual stream at a validated layer, dose-normalized to the layer's median residual norm.

Usage

pip install torch transformers
python farm_runtime.py . --chat          # or: python farm_runtime.py . "Who are you?"
python farm_runtime.py . --alpha 0.5 "Who are you?"   # dose override

Persona-stack measurements

identity	catch/100w	register	QA	neutral NLL
0	0.0	1.27	0.8	3.82

Scoring: regex/lexicon judge, symmetric across arms — arm-vs-arm deltas are meaningful, absolute numbers are indicative. QA = 5-question factual mini-suite. NLL = token loss on a neutral corpus (higher = more capability damage).

Dose & safety

• alpha 0.5-1.0 is the active range; above ~1.5 the model degrades (see the dose scans in the lab README).
• Steers style/register; identity claims do not switch on (the identity gate finding) — expect a tone shift, not a character swap.

Provenance & rights

• Persona corpus: quote/aphorism collections in the lab's data/ (fan-archived public statements).
• Trained/derived by the Arnold Persona Lab harness, Qwen/Qwen2.5-1.5B-Instruct base.

ModelFarm packages are research artifacts. Real-person personas are likeness studies for interpretability research, not impersonation products: no commercial use, do not represent outputs as statements by the real person. Prefer fictional personas for public roleplay use.

Method note for steering packages

Steering packages do not modify weights: the base model is loaded unchanged and a runtime hook applies the persona direction / neuron recipe at inference. Dose can be varied live (--alpha / --dose), and the base model stays swappable for equal-size checkpoints of the same family.