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  <meta name="description" content="Choose an official Occamy checkpoint, compare file sizes, download weights and copy deployment commands.">
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    <a class="brand" href="https://accio-lab.github.io/occamy/" target="_blank" rel="noopener noreferrer">Occamy <span>/</span> Checkpoints</a>
    <nav aria-label="Project links"><a id="collection-link" href="https://huggingface.co/Accio-Lab" target="_blank" rel="noopener noreferrer">Collection ↗</a><a href="https://huggingface.co/Accio-Lab/occamy-1.0" target="_blank" rel="noopener noreferrer">Model card ↗</a><a href="https://arxiv.org/abs/2609.11977" target="_blank" rel="noopener noreferrer">Paper ↗</a></nav>
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        <div class="hero-accio-logo"><img src="https://accio-lab.github.io/occamy/brand/accio.svg" alt="Accio"></div>
        <h1 aria-label="Occamy-1.0"><span class="hero-occamy-wordmark"><img src="https://accio-lab.github.io/occamy/brand/occamy.png" alt="" aria-hidden="true"><span>ccamy-1.0</span></span></h1>
        <p class="hero-subtitle">Choose a checkpoint.<br>Run Occamy on your hardware.</p>
        <p class="hero-deck">Compare weight files, download an official release, and copy the command for your runtime.</p>
        <div class="hero-facts"><span><b>35B</b> total parameters</span><span><b>3B</b> active per token</span><span><b>24</b> GGUF options</span><span><b>8</b> MLX candidates</span></div>
        <div class="hero-actions"><a class="button button-primary" href="#explorer-title">Choose a checkpoint <span aria-hidden="true">↓</span></a><a class="button button-secondary" href="https://huggingface.co/papers/2609.11977" target="_blank" rel="noopener noreferrer">Read the paper ↗</a></div>
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    <section class="explorer" aria-labelledby="explorer-title">
      <div class="section-heading"><div><p class="eyebrow">CHECKPOINT EXPLORER</p><h2 id="explorer-title" tabindex="-1">Choose your runtime</h2></div><span class="live-label"><i></i> Official Accio-Lab releases</span></div>
      <div class="platform-tabs" role="tablist" aria-label="Runtime platform">
        <button role="tab" id="tab-gguf" aria-selected="true" aria-controls="checkpoint-panel" data-platform="gguf">GGUF <span>llama.cpp</span></button>
        <button role="tab" id="tab-nvidia" aria-selected="false" aria-controls="checkpoint-panel" data-platform="nvidia" tabindex="-1">NVIDIA <span>GPU servers</span></button>
        <button role="tab" id="tab-mlx" aria-selected="false" aria-controls="checkpoint-panel" data-platform="mlx" tabindex="-1">Apple Silicon <span>MLX candidates</span></button>
        <button role="tab" id="tab-research" aria-selected="false" aria-controls="checkpoint-panel" data-platform="research" tabindex="-1">MTP <span>Experimental head</span></button>
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      <div id="checkpoint-panel" role="tabpanel" aria-labelledby="tab-gguf">
        <div class="filter-bar"><label class="budget-label" for="budget">Weight budget <span class="budget-field"><input id="budget" type="number" min="0" step="any" placeholder="No limit"><span>GiB</span></span></label><label class="vision-toggle"><input type="checkbox" id="vision">Include vision projector <span>+0.838 GiB</span></label><p>File sizes only. Leave extra memory for KV cache and the runtime.</p></div>
        <p id="platform-note" class="platform-note"></p>
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          <div class="checkpoint-list"><div class="list-heading"><span>CHECKPOINT</span><span>WEIGHTS</span></div><div id="model-list" aria-label="Available checkpoints"></div><p id="result-count" class="result-count" aria-live="polite"></p></div>
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    <section class="context-strip"><div><span class="small-index">01</span><h3>Weights are only the beginning.</h3><p>Context length, parallel requests and image input all add memory. Use a smaller context first and tune for your workload.</p></div><div><span class="small-index">02</span><h3>Read the validation scope.</h3><p>GGUF, FP8 and NVFP4 have format-specific checks. MLX Mac acceptance is pending; the MTP head needs a patched runtime.</p></div><div><span class="small-index">03</span><h3>Build on an open stack.</h3><p>Connect a local server to your tools through an OpenAI-compatible API. Occamy's training framework is open source.</p><a href="https://github.com/Accio-Lab/Dressage" target="_blank" rel="noopener noreferrer">Explore Dressage ↗</a></div></section>
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  <footer><span>ACCIO LAB · OCCAMY 1.0</span><span>Apache 2.0 · A browser-based deployment guide</span><a id="mlx-collection-link" href="https://huggingface.co/Accio-Lab" target="_blank" rel="noopener noreferrer">MLX collection ↗</a></footer>
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