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(max-width: 700px) 80vw, (-webkit-min-device-pixel-ratio: 2.5) and (max-width: 700px) 80vw, (min-resolution: 2dppx) and (max-width: 700px) 100vw, (-webkit-min-device-pixel-ratio: 2) and (max-width: 700px) 100vw, 700px"/><img alt="" class="bh mm op c" width="700" height="151" loading="lazy" role="presentation"/></picture></div></div><figcaption class="oq ff or oc od os ot bf b bg z du">Photo by Allenai</figcaption></figure><h1 id="ded9" class="ou ov gz bf ow ox oy hv oz pa pb hy pc pd pe pf pg ph pi pj pk pl pm pn po pp bk">Introduction</h1><p id="f31b" class="pw-post-body-paragraph nf ng gz nh b ht pq nj nk hw pr nm nn no ps nq nr ns pt nu nv nw pu ny nz oa gs bk">In a rapidly evolving AI landscape, one of the most groundbreaking developments has come from the <strong class="nh ha">Allen Institute for AI (AI2)</strong>, with the release of <strong class="nh ha">TÜLU 3</strong> — a family of open-source post-trained language models. Built upon Meta’s <strong class="nh ha">Llama 3.1</strong> architecture, TÜLU 3 takes AI’s capabilities to new heights, focusing on areas like <strong class="nh ha">reasoning</strong>, <strong class="nh ha">mathematics</strong>, <strong class="nh ha">coding</strong>, and <strong class="nh ha">safety</strong>. Unlike many proprietary models, TÜLU 3 offers complete transparency by releasing not just the models themselves, but also the datasets, training recipes, and evaluation tools used to build them. This openness makes TÜLU 3 a significant leap in democratizing high-performance AI.</p><h1 id="3ae9" class="ou ov gz bf ow ox oy hv oz pa pb hy pc pd pe pf pg ph pi pj pk pl pm pn po pp bk">The Evolution of Post-Training</h1><p id="f6f7" class="pw-post-body-paragraph nf ng gz nh b ht pq nj nk hw pr nm nn no ps nq nr ns pt nu nv nw pu ny nz oa gs bk">Post-training has become a crucial step in developing state-of-the-art language models. 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