Steelskull
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README.md
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<!DOCTYPE html>
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<html lang="en">
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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>G2-MS-Nyxora-27b Data Card</title>
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<link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
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<style>
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body, html {
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height: 100%;
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margin: 0;
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padding: 0;
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font-family: 'Quicksand', sans-serif;
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background: linear-gradient(135deg, #0a1128 0%, #1c2541 100%);
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color: #e0e1dd;
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font-size: 16px;
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}
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.container {
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width: 100%;
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height: 100%;
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padding: 20px;
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margin: 0;
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background-color: rgba(255, 255, 255, 0.05);
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border-radius: 12px;
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box-shadow: 0 4px 10px rgba(0, 0, 0, 0.3);
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backdrop-filter: blur(10px);
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border: 1px solid rgba(255, 255, 255, 0.1);
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}
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.header h1 {
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font-size: 28px;
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color: #4cc9f0;
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margin: 0 0 20px 0;
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text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
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}
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font-size: 24px;
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color: #7209b7;
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font-size: 16px;
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line-height: 1.6;
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color: #e0e1dd;
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width: 100%;
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text-decoration: none;
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color: #f72585;
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display: inline-block;
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background-color: #3a0ca3;
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color: #e0e1dd;
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padding: 10px 20px;
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border-radius: 5px;
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cursor: pointer;
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text-decoration: none;
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}
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background-color: #7209b7;
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}
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pre {
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background-color: #1c2541;
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padding: 10px;
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border-radius: 5px;
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overflow-x: auto;
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}
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code {
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font-family: 'Courier New', monospace;
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color: #e0e1dd;
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}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>G2-MS-Nyxora-27b</h1>
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</div>
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<div class="info">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/rqcAEjzvLpQwu2Cg3g1hH.png" alt="Model Image">
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<p>Now that the cute anime girl has your attention.</p>
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<p><strong>Creator:</strong> <a href="https://huggingface.co/Steelskull" target="_blank">SteelSkull</a></p>
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<h1>About G2-MS-Nyxora-27b:</h1>
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<pre><code><strong>Model Name Legend =</strong>
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"G2 = Gemma 2"
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"MS = Model_stock"</code></pre>
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<p>This model represents an experimental foray into 27b models. Feedback is welcome for further improvements.</p>
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<p>G2-MS-Nyxora-27b combines multiple models' strengths to provide a versatile assistant for various tasks, including general use, storytelling, roleplay, and mature content.</p>
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<p>The Model_stock merge method ensures the model remains focused, tailored, and high-quality.</p>
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<h2>Quants:</h2>
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<p>Will add once found</p>
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<h3>Config:</h3>
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<pre><code>MODEL_NAME = "G2-MS-Nyxora-27b"
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yaml_config = """
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base_model: google/gemma-2-27b-it
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merge_method: model_stock
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dtype: bfloat16
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models:
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- model: TheDrummer/Big-Tiger-Gemma-27B-v1
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- model: migtissera/Tess-v2.5-Gemma-2-27B-alpha
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"""
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</code></pre>
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<h4>Source Model Details:</h4>
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<p><strong>TheDrummer/Big-Tiger-Gemma-27B-v1:</strong><br>
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A decensored version of the Gemma 27B model.
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</p>
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<p><strong>migtissera/Tess-v2.5-Gemma-2-27B-alpha:</strong><br>
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The latest state-of-the-art model in the Tess series, Tess-v2.5.2, offers significant improvements in reasoning, coding, and mathematics. It ranks #1 on the MMLU benchmark among open weight models and outperforms several frontier closed models.
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</p>
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<p><strong>Gemma-2-27b-it:</strong><br>
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A lightweight, state-of-the-art model from Google, well-suited for various text generation tasks. Its small size allows deployment in resource-limited environments, fostering AI innovation for all.
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</p>
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<h4>Merge Method Details:</h4>
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<p>Model_stock Uses some neat geometric properties of fine tuned models to compute good weights for linear interpolation.</p>
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</div>
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</div>
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</body>
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</html>
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