DeepMount00
/

Alireo-400m-instruct-v0.1

@@ -1,41 +1,118 @@
-# Alireo-400M Model Card 📚
-## Model Description
-Alireo-400M is a lightweight yet powerful Italian language model with 400M parameters, designed to provide efficient natural language processing capabilities while maintaining a smaller footprint compared to larger models.
-## Key Features
-- **Architecture**: Transformer-based language model
-- **Parameters**: 400M
-- **Context Window**: 8K tokens
-- **Training Data**: Curated Italian text corpus (books, articles, web content)
-- **Model Size**: ~800MB
-## Performance
-Despite its compact size, Alireo-400M demonstrates impressive performance:
-- Outperforms Qwen 0.5B across multiple benchmarks
-- Maintains high accuracy in Italian language understanding tasks
-- Efficient inference speed due to optimized architecture
-## Limitations
-- Limited context window compared to larger models
-- May struggle with highly specialized technical content
-- Performance may vary on dialectal variations
-- Not suitable for multilingual tasks
-## Hardware Requirements
-- Minimum RAM: 2GB
-- Recommended RAM: 4GB
-- GPU: Optional, but recommended for faster inference
-- Disk Space: ~1GB (including model and dependencies)
-## License
-Apache 2.0
-## Citation
-```bibtex
-@software{alireo2024,
   author = {[Michele Montebovi]},
   title = {Alireo-400M: A Lightweight Italian Language Model},
   year = {2024},
-}
-```

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <style>
+        body {
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            line-height: 1.6;
+            max-width: 800px;
+            margin: 0 auto;
+            padding: 20px;
+            background-color: #f5f5f5;
+        }
+        .container {
+            background-color: white;
+            padding: 30px;
+            border-radius: 10px;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+        h1 {
+            color: #2c3e50;
+            border-bottom: 2px solid #3498db;
+            padding-bottom: 10px;
+            margin-bottom: 30px;
+        }
+        h2 {
+            color: #2980b9;
+            margin-top: 25px;
+        }
+        .features-list {
+            background-color: #f8f9fa;
+            padding: 20px;
+            border-radius: 5px;
+            border-left: 4px solid #3498db;
+        }
+        .citation {
+            background-color: #f8f9fa;
+            padding: 15px;
+            border-radius: 5px;
+            font-family: monospace;
+            white-space: pre-wrap;
+        }
+        .performance {
+            margin: 20px 0;
+        }
+        .limitations {
+            background-color: #fff3f3;
+            padding: 20px;
+            border-radius: 5px;
+            border-left: 4px solid #e74c3c;
+        }
+        .requirements {
+            background-color: #f0f9ff;
+            padding: 20px;
+            border-radius: 5px;
+            border-left: 4px solid #2ecc71;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>🤖 Alireo-400M Model Card</h1>
+        <h2>📝 Model Description</h2>
+        <p>Alireo-400M is a lightweight yet powerful Italian language model with 400M parameters, designed to provide efficient natural language processing capabilities while maintaining a smaller footprint compared to larger models.</p>
+        <h2>✨ Key Features</h2>
+        <div class="features-list">
+            <ul>
+                <li>🏗️ <strong>Architecture:</strong> Transformer-based language model</li>
+                <li>📊 <strong>Parameters:</strong> 400M</li>
+                <li>🪟 <strong>Context Window:</strong> 8K tokens</li>
+                <li>📚 <strong>Training Data:</strong> Curated Italian text corpus (books, articles, web content)</li>
+                <li>💾 <strong>Model Size:</strong> ~800MB</li>
+            </ul>
+        </div>
+        <h2>📈 Performance</h2>
+        <div class="performance">
+            <p>Despite its compact size, Alireo-400M demonstrates impressive performance:</p>
+            <ul>
+                <li>🏆 Outperforms Qwen 0.5B across multiple benchmarks</li>
+                <li>🎯 Maintains high accuracy in Italian language understanding tasks</li>
+                <li>⚡ Efficient inference speed due to optimized architecture</li>
+            </ul>
+        </div>
+        <h2>⚠️ Limitations</h2>
+        <div class="limitations">
+            <ul>
+                <li>Limited context window compared to larger models</li>
+                <li>May struggle with highly specialized technical content</li>
+                <li>Performance may vary on dialectal variations</li>
+                <li>Not suitable for multilingual tasks</li>
+            </ul>
+        </div>
+        <h2>💻 Hardware Requirements</h2>
+        <div class="requirements">
+            <ul>
+                <li>🎮 <strong>Minimum RAM:</strong> 2GB</li>
+                <li>💪 <strong>Recommended RAM:</strong> 4GB</li>
+                <li>🎨 <strong>GPU:</strong> Optional, but recommended for faster inference</li>
+                <li>💿 <strong>Disk Space:</strong> ~1GB (including model and dependencies)</li>
+            </ul>
+        </div>
+        <h2>📜 License</h2>
+        <p>Apache 2.0</p>
+        <h2>📄 Citation</h2>
+        <div class="citation">@software{alireo2024,
   author = {[Michele Montebovi]},
   title = {Alireo-400M: A Lightweight Italian Language Model},
   year = {2024},
+}</div>
+    </div>
+</body>
+</html>