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+ ---
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+ license: apache-2.0
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+ base_model:
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+ - Delta-Vector/Austral-SFT-KTO
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+ language:
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+ - en
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+ library_name: transformers
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+ tags:
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+ - roleplay
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+ - finetune
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+ - axolotl
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+ - adventure
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+ - creative-writing
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+ - Mistral
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+ - 24B
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+ ---
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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>Austral 24B Winton</title>
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+ <link href="" rel="stylesheet">
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+ <style>
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+ body {
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+ font-family: 'Roboto Slab', serif;
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+ background: linear-gradient(135deg, #8B4513 0%, #A0522D 25%, #CD853F 50%, #D2691E 75%, #8B4513 100%);
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+ background-size: 400% 400%;
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+ animation: prehistoricShift 20s ease-in-out infinite;
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+ color: #2F1B14;
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+ margin: 0;
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+ padding: 0;
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+ font-size: 16px;
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+ min-height: 100vh;
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+ }
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+ @keyframes prehistoricShift {
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+ 0%, 100% { background-position: 0% 50%; }
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+ 50% { background-position: 100% 50%; }
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+ }
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+ .container {
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+ margin: 20px;
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+ background: linear-gradient(145deg, #F4E4BC 0%, #DEB887 100%);
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+ padding: 20px;
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+ border-radius: 15px;
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+ box-shadow: 0 8px 25px rgba(0, 0, 0, 0.4), inset 0 2px 5px rgba(255, 255, 255, 0.3);
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+ border: 4px solid #8B4513;
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+ position: relative;
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+ overflow: hidden;
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+ }
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+ .container::before {
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+ content: '';
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+ position: absolute;
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+ top: 0;
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+ left: 0;
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+ right: 0;
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+ bottom: 0;
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+ background-image:
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+ radial-gradient(circle at 20% 80%, rgba(139, 69, 19, 0.1) 0%, transparent 50%),
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+ radial-gradient(circle at 80% 20%, rgba(160, 82, 45, 0.1) 0%, transparent 50%);
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+ pointer-events: none;
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+ }
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+ .header h1 {
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+ font-family: 'Cinzel', serif;
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+ font-size: 32px;
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+ color: #5D2E0C;
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+ margin: 0 0 20px 0;
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+ text-align: center;
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+ text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
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+ letter-spacing: 2px;
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+ position: relative;
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+ }
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+ .section {
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+ margin-top: 30px;
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+ position: relative;
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+ }
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+ .section h2 {
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+ font-family: 'Cinzel', serif;
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+ font-size: 26px;
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+ color: #5D2E0C;
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+ text-align: center;
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+ margin-bottom: 20px;
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+ text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2);
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+ letter-spacing: 1px;
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+ }
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+ .info p {
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+ color: #2F1B14;
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+ line-height: 1.7;
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+ font-size: 16px;
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+ text-shadow: 0 1px 1px rgba(255, 255, 255, 0.5);
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+ }
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+ .info img {
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+ width: 85%;
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+ border-radius: 12px;
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+ margin: 0 auto 15px;
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+ display: block;
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+ box-shadow: 0 0 25px rgba(0, 0, 0, 0.4);
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+ border: 3px solid #8B4513;
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+ filter: sepia(20%) contrast(110%);
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+ }
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+ a {
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+ color: #5D2E0C;
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+ text-decoration: none;
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+ transition: all 0.3s ease;
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+ font-weight: 500;
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+ }
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+ a:hover {
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+ color: #8B4513;
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+ text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2);
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+ }
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+ .button {
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+ display: inline-block;
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+ background: linear-gradient(145deg, #CD853F, #D2691E);
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+ color: #2F1B14;
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+ padding: 12px 24px;
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+ border-radius: 8px;
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+ cursor: pointer;
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+ text-decoration: none;
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+ transition: all 0.3s ease;
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+ box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
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+ border: 2px solid #8B4513;
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+ }
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+ .button:hover {
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+ background: linear-gradient(145deg, #D2691E, #CD853F);
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+ box-shadow: 0 6px 15px rgba(139, 69, 19, 0.4);
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+ transform: translateY(-2px);
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+ }
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+ pre {
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+ background: linear-gradient(145deg, #F5DEB3, #DEB887);
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+ padding: 20px;
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+ border-radius: 8px;
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+ overflow-x: auto;
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+ border: 2px solid #8B4513;
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+ box-shadow: inset 0 2px 5px rgba(0, 0, 0, 0.1);
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+ }
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+ code {
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+ font-family: 'Courier New', monospace;
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+ color: #2F1B14;
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+ }
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+ .info-card {
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+ background: linear-gradient(145deg, #F5DEB3, #DEB887);
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+ border: 3px solid #8B4513;
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+ border-radius: 12px;
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+ overflow: hidden;
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+ box-shadow: 0 6px 15px rgba(0, 0, 0, 0.2);
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+ }
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+ .info-header {
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+ background: linear-gradient(145deg, #CD853F, #D2691E);
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+ padding: 25px;
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+ border-bottom: 2px solid #8B4513;
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+ }
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+ .info-header h3 {
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+ font-family: 'Cinzel', serif;
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+ color: #2F1B14;
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+ margin: 0 0 15px 0;
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+ font-size: 22px;
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+ text-align: center;
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+ text-shadow: 1px 1px 2px rgba(0, 0, 0, 0.2);
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+ letter-spacing: 1px;
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+ }
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+ .model-tags {
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+ display: flex;
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+ gap: 10px;
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+ flex-wrap: wrap;
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+ justify-content: center;
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+ }
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+ .model-tag {
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+ background: linear-gradient(145deg, #DEB887, #CD853F);
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+ color: #2F1B14;
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+ padding: 6px 12px;
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+ border-radius: 6px;
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+ font-size: 12px;
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+ border: 2px solid #8B4513;
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+ font-weight: 500;
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+ box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
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+ }
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+ .model-composition {
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+ padding: 25px;
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+ border-bottom: 2px solid #8B4513;
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+ }
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+ .model-composition h4 {
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+ font-family: 'Cinzel', serif;
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+ color: #5D2E0C;
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+ margin: 0 0 20px 0;
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+ font-size: 18px;
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+ text-align: center;
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+ letter-spacing: 1px;
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+ }
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+ .composition-list {
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+ list-style: none;
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+ padding: 0;
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+ margin: 0;
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+ display: grid;
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+ gap: 15px;
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+ }
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+ .composition-list li {
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+ color: #2F1B14;
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+ display: flex;
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+ align-items: baseline;
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+ gap: 12px;
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+ padding: 10px;
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+ background: rgba(245, 222, 179, 0.5);
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+ border-radius: 6px;
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+ border-left: 4px solid #8B4513;
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+ }
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+ .model-component {
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+ font-weight: 600;
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+ min-width: 120px;
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+ }
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+ .model-description {
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+ padding: 25px;
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+ background: linear-gradient(145deg, #F5DEB3, #F4E4BC);
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+ }
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+ .metrics-section {
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+ margin-bottom: 30px;
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+ }
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+ .metrics-section details {
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+ background: linear-gradient(145deg, #F5DEB3, #DEB887);
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+ border: 3px solid #8B4513;
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+ border-radius: 10px;
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+ padding: 20px;
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+ margin-bottom: 20px;
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+ box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2);
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+ }
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+ .metrics-section summary {
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+ font-family: 'Cinzel', serif;
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+ color: #5D2E0C;
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+ font-size: 18px;
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+ cursor: pointer;
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+ outline: none;
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+ padding: 10px 0;
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+ text-align: center;
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+ font-weight: 500;
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+ letter-spacing: 1px;
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+ }
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+ .creator-section {
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+ margin: 25px 0;
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+ text-align: center;
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+ }
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+ .creator-badge {
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+ display: inline-flex;
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+ align-items: center;
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+ background: linear-gradient(145deg, #CD853F, #D2691E);
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+ border: 3px solid #8B4513;
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+ border-radius: 10px;
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+ padding: 15px 20px;
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+ box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2);
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+ }
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+ .creator-label {
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+ color: #2F1B14;
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+ font-size: 14px;
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+ margin-right: 10px;
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+ font-weight: 500;
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+ }
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+ .creator-link {
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+ display: flex;
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+ align-items: center;
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+ gap: 8px;
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+ color: #2F1B14;
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+ text-decoration: none;
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+ transition: all 0.3s ease;
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+ }
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+ .creator-name {
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+ font-weight: 600;
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+ }
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+ .creator-arrow {
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+ font-size: 16px;
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+ transition: transform 0.3s ease;
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+ }
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+ .creator-link:hover .creator-arrow {
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+ transform: translateX(5px);
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+ }
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+ .link-arrow {
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+ display: inline-block;
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+ transition: transform 0.3s ease;
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+ }
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+ a:hover .link-arrow {
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+ transform: translateX(3px);
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+ }
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+ .axolotl-container {
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+ text-align: center;
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+ margin: 35px 0;
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+ }
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+ .axolotl-container img {
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+ max-width: 300px;
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+ border-radius: 10px;
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+ box-shadow: 0 6px 15px rgba(0, 0, 0, 0.3);
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+ border: 3px solid #8B4513;
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+ filter: sepia(30%) contrast(110%);
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+ }
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+ .fossil-texture {
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+ position: relative;
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+ }
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+ .fossil-texture::after {
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+ content: '';
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+ position: absolute;
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+ top: 0;
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+ left: 0;
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+ right: 0;
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+ bottom: 0;
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+ background-image:
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+ radial-gradient(circle at 25% 25%, rgba(139, 69, 19, 0.05) 2px, transparent 2px),
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+ radial-gradient(circle at 75% 75%, rgba(160, 82, 45, 0.05) 1px, transparent 1px);
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+ background-size: 50px 50px, 30px 30px;
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+ pointer-events: none;
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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 fossil-texture">
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+ <div class="header">
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+ <h1>Austral 24B Winton</h1>
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+ </p>
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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/66c26b6fb01b19d8c3c2467b/jxUvuFK1bdOdAPiYIcBW5.jpeg" alt="Model banner">
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+ <div style="text-align: center;">
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+ <div class="creator-section">
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+ <div class="creator-badge">
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+ <span class="creator-label">Trained by</span>
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+ <a href="https://huggingface.co/Delta-Vector" target="_blank" class="creator-link">
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+ <span class="creator-name">Delta-Vector</span>
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+ </a>
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+ </div>
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+ </div>
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+ <div class="model-info">
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+ <h2>Overview</h2>
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+ <div class="info-card">
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+ <div class="info-header">
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+ <h3>Austral 24B - Winton</h3>
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+ <div class="model-tags">
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+ <span class="model-tag">Codex Finetune</span>
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+ <span class="model-tag">Mistral Based</span>
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+ <span class ="model-tag">KTO enhanced</span>
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+ <span class ="model-tag">Adventure/Roleplay generalist</span>
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+ <span class="model-tag">24B Sized model</span>
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+ </div>
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+ </div>
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+ <div class="model-description">
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+ <p style="font-weight: bold; font-style: italic;">More than 1.5-metres tall, about six-metres long and up to 1000-kilograms heavy, Australovenator Wintonensis was a fast and agile hunter. The largest known Australian theropod.</p>
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+ <p>This is a finetune of Codex 24B to be a generalist Roleplay/Adventure model. I've removed some of the "slops" that i noticed in an otherwise great model aswell as improving the general writing of the model, This was a multi-stage finetune, all previous checkpoints are released aswell. In testing it has shown to be a great model for Adventure cards & Roleplay, Often pushing the plot forward better then other models, While avoiding some of the slops you'd find in models from Drummer and Co.</p>
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+ <p>Support my finetunes / Me on Kofi: https://Ko-fi.com/deltavector | Thank you to Auri for helping/Testing ♥</p>
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+ </div>
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+ </div>
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+ </div>
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+ <div class="section">
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+ <h2>Quants</h2>
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+ <div class="info-card">
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+ <div class="model-composition">
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+ <h4>Quants Formats</h4>
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+ <ul class="composition-list">
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+ <li><span class="model-component"><a href="" target="_blank">GGUF</a></span>For use with LLama.cpp & Forks (coming soon!))</li>
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+ <li><span class="model-component"><a href="" target="_blank">EXL3</a></span>For use with TabbyAPI (Coming soon!)</li>
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+ </ul>
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+ </div>
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+ </div>
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+ </div>
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+ <div class="section">
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+ <h2>Chat Format</h2>
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+ <p>This model utilizes ChatML.</p>
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+ <pre><code><|im_start|>user
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+ Hi there!<|im_end|>
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+ <|im_start|>assistant
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+ Nice to meet you!<|im_end|>
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+ <|im_start|>user
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+ Can I ask a question?<|im_end|>
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+ <|im_start|>assistant</code></pre>
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+ </div>
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+ <div class="section">
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+ <h2>Training</h2>
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+ <p>As the the Austral/Francois tradition, I built off another great finetune Harbinger-24B, I did 4 epochs ontop with roughly the same datamix as Francois-Huali/Austral 70B as a R128 Lora, then KTO alignment with a mix of Instruct/Small writing datasets and then finally another 4 epoch SFT with Rep_remover (Thanks Pocket!)</p>
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+ <div class="metrics-section">
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+ <details>
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+ <summary>Config(Post-KTO SFT)</summary>
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+ <pre><code>https://wandb.ai/new-eden/austral/runs/i85da0c6?nw=nwuserdeltavector</code></pre>
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+ </details>
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+ </div>
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+ </div>
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+ <div class="section">
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+ <h2Fossil Formation Process</h2>
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+ <p>This model was trained over 4 epochs using 8 x A100s (Ty to my work, Cognitive Computations) for the base SFT, Then i used KTO to clean up some coherency issues for 1 epoch, then finally training for another 4 epochs on Rep_Remover to delete slops. Total was roughly 80 hours total.</p>
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+ <p style="text-align: center; margin-top: 20px;">
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+ <div class="axolotl-container">
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+ <a href="https://github.com/OpenAccess-AI-Collective/axolotl" target="_blank">
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+ <img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl">
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+ </a>
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+ </div>
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+ <div class="section">
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+ <h2>Credits</h2>
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+ <p>TYSM to my friends: Auri, Lucy, Trappu, Alicat, Kubernetes Bad, Intervitens, NyxKrage & Kalomaze</p>
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+ </p>
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+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </body>
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+ </html>