Apply item 0x054ca82f for issue #7
Squash of the patch of item 0x054ca82fe89ff53664b84304b335f216bd1dfbeca76588ee9d0169e905dac9ef, final in the elffuss ledger. Solver 0xa472b6bac297911f562335db561c6cbf33e5c32e; 2 approvals of round 0. T2T-Item: 0x054ca82fe89ff53664b84304b335f216bd1dfbeca76588ee9d0169e905dac9ef T2T-Issue: 0x7bf84a053d2bd6ce83a7ce9d2799aadf280de622b31dbf03026d0e69d76d3a9a T2T-Event: 0xc4d14ab5f340035493bca3a09c233287a16a2fd49c720b5d91e1fae2301ccfd7
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@@ -12,6 +12,7 @@
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// el de juegos ejecuta el juego generado y lo puntúa mirándolo correr.
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import { DEFAULTS, packHistoryACER, estimateTokens } from './acer-core.js';
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import { TASKS } from './swe-tasks.js';
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import { MODELS } from './providers/litert.js';
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const $ = s => document.querySelector(s);
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const el = (t, c, x) => { const n = document.createElement(t); if (c) n.className = c; if (x != null) n.textContent = x; return n; };
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@@ -68,8 +69,7 @@ const BENCHES = [
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const BRAINS = [
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['rules', 'Reglas (sin GPU)', 'Determinista. Valida el arnés sin bajar pesos.'],
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['onnx', 'Elffuss LM (CPU/wasm)', 'LFM2.5-1.2B por transformers.js.'],
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['litert:gemma-e2b', 'Gemma-4 E2B (~2 GB)', 'WebGPU.'],
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['litert:gemma-e4b', 'Gemma-4 E4B (~3 GB)', 'WebGPU. El mejor.'],
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...['gemma-e2b', 'gemma-e4b'].map(k => ['litert:' + k, MODELS[k].label, MODELS[k].tag]),
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];
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// ─────────────────────────── consola ───────────────────────────
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