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<h1>Vortex Language Model (VLM) Documentation</h1>
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<h2>Overview</h2>
<p><strong>VLM</strong> stands for <strong>Vortex Language Model</strong>, a series of transformer-based models developed by <strong>Vortex Intelligence</strong>. The models are designed for tasks such as text generation, reasoning, and instruction following. Each version of VLM is structured in three training stages for progressive refinement.</p>
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<p><strong>Note on Hardware:</strong> Training is performed on different GPU configurations depending on availability - sometimes using 1× NVIDIA RTX A5000, sometimes 1× A40, and occasionally 1× RTX 5060 Ti with 16GB VRAM.</p>
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<h2>Model Structure</h2>
<p>Each VLM version follows a three-stage pipeline:</p>
<ul>
<li><strong>K1</strong>: Trained from scratch (base model)</li>
<li><strong>K2</strong>: Fine-tuned on broader/general-purpose data</li>
<li><strong>K3</strong>: Fine-tuned for clarity and simplicity</li>
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<p>K stands for <em>Knowledge</em>, with higher numbers representing more advanced training stages. <strong>Higher doesn't mean the model has more parameters!</strong></p>
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<h2>Versions and Training Details</h2>
<h3>VLM 1</h3>
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<li>Parameters: <code>124M</code></li>
<li>Training Time: ~4 hours per stage</li>
<li>Final Loss (all stages): ~<code>3.0</code></li>
<li><strong>K1</strong>: Trained on <code>tatsu-lab/alpaca</code> and a small custom dataset</li>
<li><strong>K2</strong>: Fine-tuned K1 on <code>Elriggs/openwebtext-100k</code></li>
<li><strong>K3</strong>: Fine-tuned K2 on <code>rahular/simple-wikipedia</code></li>
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<h3>VLM 1.1</h3>
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<li>Parameters: <code>355M</code></li>
<li>Training Time: ~4 hours per stage</li>
<li>Target Final Loss: ~<code>1.0</code></li>
<li><strong>K1</strong>: Currently training on <code>------</code> and <code>------</code></li>
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<h2>Contact & More</h2>
<p>Developed and maintained by <strong>Vortex Intelligence</strong>.</p>
<!-- <p>Website: <a href="https://pingvortex.xyz" target="_blank">pingvortex.xyz</a></p> -->
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