Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,626 @@
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---
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license: mit
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1 |
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---
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2 |
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license: mit
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datasets:
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- ServiceNow-AI/R1-Distill-SFT
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language:
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- en
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
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pipeline_tag: text-generation
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library_name: transformers
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---
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<!DOCTYPE html>
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<style>
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ebody {
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font-family: 'Quicksand', sans-serif;
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background: linear-gradient(135deg, #FF69B4 0%, #800080 100%);
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color: #FFFFFF;
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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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.container {
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margin: 20px;
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background-color: rgba(28, 14, 36, 0.95);
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padding: 20px;
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border-radius: 12px;
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box-shadow: 0 4px 20px rgba(255, 105, 180, 0.4);
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border: 1px solid rgba(255, 105, 180, 0.4);
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outline: 1px solid rgba(255, 105, 180, 0.7);
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outline-offset: -1px;
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position: relative;
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backdrop-filter: blur(10px);
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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: -1px;
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left: -1px;
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right: -1px;
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bottom: -1px;
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border: 1px solid rgba(255, 105, 180, 0.98);
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border-radius: 12px;
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pointer-events: none;
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animation: borderGlow 2s ease-in-out infinite;
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}
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@keyframes borderGlow {
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0% {
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box-shadow: 0 0 5px rgba(255, 105, 180, 0.98);
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}
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50% {
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box-shadow: 0 0 20px rgba(255, 105, 180, 0.98);
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}
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100% {
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box-shadow: 0 0 5px rgba(255, 105, 180, 0.98);
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}
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}
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.header h1 {
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font-size: 28px;
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color: #FF69B4;
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margin: 0 0 20px 0;
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text-shadow: 0 0 15px rgba(255, 105, 180, 0.8);
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letter-spacing: 1px;
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}
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.update-section {
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margin-top: 30px;
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}
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.update-section h2, h2 {
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font-size: 24px;
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color: #FF69B4;
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text-shadow: 0 0 15px rgba(255, 105, 180, 0.8);
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letter-spacing: 0.5px;
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}
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.update-section p {
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font-size: 16px;
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line-height: 1.6;
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color: #FFE1FF;
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}
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.info p {
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color: #FFE1FF;
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line-height: 1.6;
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font-size: 16px;
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}
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.info img {
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width: 100%;
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border-radius: 10px;
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margin-bottom: 15px;
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box-shadow: 0 0 30px rgba(255, 105, 180, 0.5);
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border: 1px solid rgba(255, 105, 180, 0.4);
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outline: 1px solid rgba(255, 105, 180, 0.7);
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outline-offset: -1px;
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transition: transform 0.3s ease, box-shadow 0.3s ease;
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}
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.info img:hover {
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transform: scale(1.01);
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box-shadow: 0 0 40px rgba(255, 105, 180, 0.6);
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}
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a {
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color: #00FFEE;
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text-decoration: none;
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transition: color 0.3s ease;
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}
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a:hover {
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color: #FF1493;
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}
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.button {
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display: inline-block;
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background: linear-gradient(45deg, rgba(255, 105, 180, 0.9), rgba(128, 0, 128, 0.9));
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color: #FFFFFF;
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padding: 12px 24px;
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border-radius: 5px;
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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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border: 1px solid rgba(255, 105, 180, 0.4);
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}
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.button:hover {
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background: linear-gradient(45deg, rgba(255, 105, 180, 1), rgba(128, 0, 128, 1));
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box-shadow: 0 0 20px rgba(255, 105, 180, 0.7);
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transform: translateY(-2px);
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}
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pre {
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background-color: rgba(28, 14, 36, 0.95);
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padding: 15px;
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border-radius: 5px;
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overflow-x: auto;
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border: 1px solid rgba(255, 20, 147, 0.3);
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outline: 1px solid rgba(255, 20, 147, 0.6);
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outline-offset: -1px;
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}
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code {
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font-family: 'Courier New', monospace;
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color: #FFE1FF;
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}
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.info-grid {
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155 |
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display: grid;
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156 |
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grid-template-columns: repeat(3, 1fr);
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157 |
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gap: 15px;
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158 |
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}
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.creator-section {
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margin: 20px 0;
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}
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.creator-badge {
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display: inline-flex;
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166 |
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align-items: center;
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background: rgba(28, 14, 36, 0.95);
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168 |
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border: 1px solid rgba(255, 20, 147, 0.3);
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169 |
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border-radius: 8px;
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padding: 10px 15px;
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}
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.creator-label {
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color: #FFE1FF;
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font-size: 14px;
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margin-right: 8px;
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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: 5px;
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183 |
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color: #00FFEE;
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184 |
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text-decoration: none;
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185 |
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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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193 |
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font-size: 16px;
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194 |
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transition: transform 0.3s ease;
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}
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.creator-link:hover {
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color: #FF1493;
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}
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.creator-link:hover .creator-arrow {
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transform: translateX(3px);
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}
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.model-info {
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margin-top: 30px;
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}
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.name-legend {
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background: rgba(28, 14, 36, 0.95);
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border: 1px solid rgba(255, 20, 147, 0.3);
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border-radius: 8px;
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padding: 20px;
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margin: 20px 0;
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}
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.name-legend h3 {
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color: #FF1493;
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font-size: 18px;
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margin: 0 0 15px 0;
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}
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.legend-grid {
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display: grid;
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225 |
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gap: 12px;
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}
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.legend-item {
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display: flex;
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230 |
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align-items: baseline;
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gap: 10px;
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}
|
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.legend-key {
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color: #00FFEE;
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font-weight: 600;
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min-width: 80px;
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}
|
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|
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.legend-value {
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color: #FFE1FF;
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}
|
243 |
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|
244 |
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.model-description {
|
245 |
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background: rgba(28, 14, 36, 0.95);
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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">
|
565 |
+
<title>Maestro-R1-Llama-8B</title>
|
566 |
+
<link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
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<body>
|
570 |
+
<div class="container">
|
571 |
+
<div class="header">
|
572 |
+
<h1>Maestro-R1-Llama-8B</h1>
|
573 |
+
</div>
|
574 |
+
<div class="info">
|
575 |
+
<img src="Maestro-Logo.png" alt="Model banner">
|
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+
<div class="creator-section">
|
577 |
+
<div class="creator-badge">
|
578 |
+
<span class="creator-label">Created by</span>
|
579 |
+
<a href="https://huggingface.co/suayptalha" target="_blank" class="creator-link">
|
580 |
+
<span class="creator-name">suayptalha</span>
|
581 |
+
<span class="creator-arrow">→</span>
|
582 |
+
</a>
|
583 |
+
</div>
|
584 |
+
</div>
|
585 |
+
<div class="model-info">
|
586 |
+
<h2>Model Information</h2>
|
587 |
+
<div class="info-card">
|
588 |
+
<div class="info-header">
|
589 |
+
<h3>Maestro-R1-Llama-8B</h3>
|
590 |
+
<div class="model-tags">
|
591 |
+
<span class="model-tag">Maestro-R1-Llama-8B</span>
|
592 |
+
<span class="model-tag">deepseek-ai/DeepSeek-R1-Distill-Llama-8B</span>
|
593 |
+
<span class="model-tag">8B Parameters</span>
|
594 |
+
</div>
|
595 |
+
</div>
|
596 |
+
<div class="model-composition">
|
597 |
+
<h4>Base Model</h4>
|
598 |
+
<ul class="composition-list">
|
599 |
+
<li><span class="model-component"><a href="deepseek-ai/DeepSeek-R1-Distill-Llama-8B" target="_blank">DeepSeek-R1-Distill-Llama-8B</a></span></li>
|
600 |
+
</ul>
|
601 |
+
</div>
|
602 |
+
<div class="model-description">
|
603 |
+
Maestro-R1-Llama-8B is a powerful language model fine-tuned from DeepSeek-R1-Distill-Llama-8B, a distilled model based on the Llama-3 architecture. DeepSeek-R1-Distill-Llama-8B itself is derived from the Llama-3 architecture, with a distillation process from DeepSeek-v3, utilizing a large corpus of diverse data. This distillation enables the model to retain strong reasoning capabilities while maintaining a smaller parameter count.
|
604 |
+
<br>
|
605 |
+
Maestro-R1-Llama-8B builds on this foundation, further enhancing its performance through fine-tuning on the ServiceNow-AI/R1-Distill-SFT dataset. This fine-tuning step sharpens the model's ability to handle specialized tasks and improves its reasoning, problem-solving, and code generation capabilities. The combination of the distilled base model and domain-specific fine-tuning makes Maestro-R1-Llama-8B an efficient and robust model, excelling across a wide range of language tasks.
|
606 |
+
</div>
|
607 |
+
<div class="model-composition">
|
608 |
+
<h4>Loss Graph</h4>
|
609 |
+
<img src="loss.png" alt="Model banner">
|
610 |
+
</div>
|
611 |
+
</div>
|
612 |
+
<div class="support-section">
|
613 |
+
<h2>Support & Community:</h2>
|
614 |
+
<div class="support-buttons">
|
615 |
+
<a href="https://buymeacoffee.com/suayptalha" target="_blank" class="button">
|
616 |
+
Buy me a coffee
|
617 |
+
</a>
|
618 |
+
<a href="https://discord.com/users/suaypt" target="_blank" class="button">
|
619 |
+
suayptalha - Discord
|
620 |
+
</a>
|
621 |
+
</div>
|
622 |
+
</div>
|
623 |
+
</div>
|
624 |
+
</div>
|
625 |
+
</body>
|
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+
</html>
|