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- Extract 14,198 training pairs from 6,941 source maps in node_modules - Train v2 model (4-layer, 192-dim, 6-head transformer, 1.9M params) - Val accuracy: 83.67% (up from 75.72%), exact match: 12.3% (up from 0.1%) - Export weights.bin (7.3MB) for Rust runtime inference - Add decompiler dashboard (React + Tailwind + Vite) - Add runnable RVF (7,350 vectors, 49 segments, witness chain) - Update evaluate-model.py to support configurable model architectures - All 13 Rust tests pass, all 45 RVF files have valid SFVR headers Co-Authored-By: claude-flow <ruv@ruv.net>
18 lines
696 B
HTML
18 lines
696 B
HTML
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<head>
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<meta charset="UTF-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<title>Decompiler Dashboard - RuVector</title>
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<link rel="preconnect" href="https://fonts.googleapis.com" />
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
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<link
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href="https://fonts.googleapis.com/css2?family=JetBrains+Mono:wght@400;500;600;700&family=Inter:wght@400;500;600;700&display=swap"
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rel="stylesheet"
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/>
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</head>
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<body class="bg-[#0a0a0f] text-gray-200 antialiased">
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<div id="root"></div>
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<script type="module" src="/src/main.tsx"></script>
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</body>
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</html>
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