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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>Pico-Type — Tiny, Byte-Level Content Classifier (1.5M params, 95.2% accuracy)</title>
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- <meta name="description" content="Pico-Type is a 1.5M-parameter byte-level multi-head classifier that identifies code language, content type, and more from raw bytes — no parsing needed. 95.2% real-world accuracy, ONNX export, open source." />
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  <meta name="keywords" content="pico-type, byte-level classifier, content classification, machine learning, tiny model, open source, code language detection, multi-head classifier" />
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  <meta property="og:title" content="Pico-Type — Tiny Byte-Level Content Classifier" />
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- <meta property="og:description" content="1.5M parameters, 95.2% real-world accuracy. Classifies raw bytes into code language, content modality, subtype, and more. No parsing, no dependencies." />
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  <meta property="og:url" content="https://eulogik.github.io/pico-type/" />
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  <meta property="og:type" content="website" />
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  <meta property="og:image" content="https://eulogik.github.io/pico-type/logo.png" />
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  <meta name="twitter:card" content="summary_large_image" />
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  <meta name="twitter:title" content="Pico-Type — Tiny Byte-Level Content Classifier" />
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- <meta name="twitter:description" content="1.5M parameters, 95.2% real-world accuracy. Classifies raw bytes into code language, content modality, subtype, and more. Open source." />
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  <link rel="canonical" href="https://eulogik.github.io/pico-type/" />
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  <link rel="icon" type="image/x-icon" href="favicon.ico" />
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  <link rel="icon" type="image/png" href="logo.png" />
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  <!-- Stats -->
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  <div class="stats container">
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  <div><div class="stat-value">1.5M</div><div class="stat-label">Parameters</div></div>
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- <div><div class="stat-value">95.2%</div><div class="stat-label">Real-World Accuracy</div></div>
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  <div><div class="stat-value">62</div><div class="stat-label">Code Languages</div></div>
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  <div><div class="stat-value">7</div><div class="stat-label">Classification Heads</div></div>
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  <div><div class="stat-value">2KB</div><div class="stat-label">Context Window</div></div>
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  <!-- Real-world accuracy -->
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  <section>
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- <h2>Real-World Accuracy: 20/21 (95.2%)</h2>
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  <p style="text-align:center;color:var(--text-muted);margin-bottom:32px;">
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- Tested against a hand-curated set covering every coarse type &mdash; from Python and JavaScript to ZIP binaries and Hindi text.
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  </p>
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  <div class="table-wrap">
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  <table>
 
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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>Pico-Type — Tiny, Byte-Level Content Classifier (1.5M params, 98.3% text-lang accuracy)</title>
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+ <meta name="description" content="Pico-Type is a 1.5M-parameter byte-level multi-head classifier that identifies code language, content type, and more from raw bytes — no parsing needed. 98.3% text-lang accuracy, ONNX export, open source." />
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  <meta name="keywords" content="pico-type, byte-level classifier, content classification, machine learning, tiny model, open source, code language detection, multi-head classifier" />
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  <meta property="og:title" content="Pico-Type — Tiny Byte-Level Content Classifier" />
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+ <meta property="og:description" content="1.5M parameters, 98.3% text-lang accuracy. Classifies raw bytes into code language, content modality, subtype, and more. No parsing, no dependencies." />
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  <meta property="og:url" content="https://eulogik.github.io/pico-type/" />
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  <meta property="og:type" content="website" />
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  <meta property="og:image" content="https://eulogik.github.io/pico-type/logo.png" />
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  <meta name="twitter:card" content="summary_large_image" />
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  <meta name="twitter:title" content="Pico-Type — Tiny Byte-Level Content Classifier" />
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+ <meta name="twitter:description" content="1.5M parameters, 98.3% text-lang accuracy. Classifies raw bytes into code language, content modality, subtype, and more. Open source." />
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  <link rel="canonical" href="https://eulogik.github.io/pico-type/" />
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  <link rel="icon" type="image/x-icon" href="favicon.ico" />
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  <link rel="icon" type="image/png" href="logo.png" />
 
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  <!-- Stats -->
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  <div class="stats container">
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  <div><div class="stat-value">1.5M</div><div class="stat-label">Parameters</div></div>
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+ <div><div class="stat-value">98.3%</div><div class="stat-label">Text-Lang Accuracy</div></div>
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  <div><div class="stat-value">62</div><div class="stat-label">Code Languages</div></div>
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  <div><div class="stat-value">7</div><div class="stat-label">Classification Heads</div></div>
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  <div><div class="stat-value">2KB</div><div class="stat-label">Context Window</div></div>
 
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  <!-- Real-world accuracy -->
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  <section>
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+ <h2>Real-World Accuracy: 60.3% code lang · 98.3% text lang</h2>
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  <p style="text-align:center;color:var(--text-muted);margin-bottom:32px;">
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+ Evaluated on real-world corpora &mdash; The Heap (1,200 code samples, 24 languages) and Wikipedia (1,500 articles, 30 languages).
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  </p>
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  <div class="table-wrap">
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  <table>