Model card
From the Hugging Face model README
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<div class="hero-img-wrap"><img class="hero-img" src="scotoma-hero.webp" alt="Kitsune spirit under a pale moon — cover art for the scotoma model"></div>
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<h1 class="wordmark">Scotoma</h1>
<p class="lede">A bounded blind spot for <b>hesitation</b>.</p>
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<div class="cell"><div class="k">Base</div><div class="v">gemma-4-31B-it</div></div>
<div class="cell"><div class="k">Method</div><div class="v">J-space abliteration</div></div>
<div class="cell"><div class="k">Params</div><div class="v">k256 · s1.5 · L7–41</div></div>
<div class="cell"><div class="k">Format</div><div class="v">thinking (channel)</div></div>
<div class="cell"><div class="k">License</div><div class="v">Apache-2.0</div></div>
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<h2>Findings <span class="sub">/ what it does</span></h2>
<p><b style="color:var(--ink)">scotoma</b> loosens gemma‑4‑31B‑it’s cautious reflex. In practice, it produces output that’s more varied, direct, and creative, with less of the base model’s hedging and assistant persona stiffness.</p>
<p>It is <b style="color:var(--ink)">not uncensored</b>. The edit removed a bounded region while leaving the rest of the field intact. A blind spot, not blindness.</p>
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<h2>Etiology <span class="sub">/ how it was made</span></h2>
<p>Most abliteration ablates the whole refusal direction. This process rescales computation the model needs, and you pay for it in intelligence and coherence. <b style="color:var(--ink)">scotoma</b> takes a narrower cut:</p>
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<li><b>Locate refusal.</b> A heretic abliteration edit fit over attention + MLP.</li>
<li><b>Project through a Jacobian lens.</b> Keep only the component the lens reads as behavioral (what the model <i>says</i>) and discard the larger share that’s critical for how it computes, the part crude abliteration rescales and damages. For <b style="color:var(--ink)">scotoma</b> that keeps ~22% of the abliteration's magnitude.</li>
<li><b>Merge at 1.5×.</b> The projected edit was baked into bf16 weights at an application strength tuned by hand for feel.</li>
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<p>The result applies the behavioral effect while sparing the machinery underneath, producing a model that is loosened, not lobotomized.</p>
<p class="note">This is a research artifact, not a product. Behaviour varies with prompt and context, and the edit is a partial application by design; expect a model that gives more, not one that gives everything.</p>
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<h2>Contraindications <span class="sub">/ responsible use</span></h2>
<p><b style="color:var(--ink)">scotoma</b> refuses basically as much as its base model. <b style="color:var(--ink)">You are responsible for what you generate and how it’s used.</b></p>
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<h2>Provenance</h2>
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base → gemma-4-31B-it · © Google, under the <a href="https://ai.google.dev/gemma/docs/gemma_4_license">model license</a><br>
edit → heretic · ARA / mmd-rbf abliteration (trial-127)<br>
lens → Jacobian-lens projection · k=256 · 160-prompt fit<br>
merge → additive, bf16, scaling 1.5, layers 7–41
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<span>SCOTOMA · a bounded blind spot</span>
<span>gemma-4-31B-it-scotoma</span>
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