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  <li><strong>Disposition Distillation</strong> — Training behavioral tendencies (planning, uncertainty acknowledgment, self-verification) into sub-billion parameter model weights via all-MIT multi-teacher distillation</li>
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  </ul>
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- <h2>Open Models</h2>
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  <table>
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  <thead>
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  <tr>
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  <td><a href="https://huggingface.co/Tinman-Lab/tinman-code-0.6B">tinman-code-0.6B</a></td>
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  <td>418 MB</td>
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- <td>Coding assistant with meta-cognitive awareness plans, verifies, flags uncertainty</td>
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  </tr>
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  </tbody>
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  </table>
 
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  <li><strong>Disposition Distillation</strong> — Training behavioral tendencies (planning, uncertainty acknowledgment, self-verification) into sub-billion parameter model weights via all-MIT multi-teacher distillation</li>
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  </ul>
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+ <h2>Research Releases</h2>
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  <table>
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  <td><a href="https://huggingface.co/Tinman-Lab/tinman-code-0.6B">tinman-code-0.6B</a></td>
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  <td>418 MB</td>
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+ <td>Research releaseDisposition Distillation proof-of-concept on Qwen3-0.6B</td>
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  </tr>
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  </tbody>
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  </table>