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README.md
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<h2 style="font-size: 32px; text-align: center;">Alireo-400M 🤖 🇮🇹</h2>
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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.
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* **Architecture**: Transformer-based language model 🏗️
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* **Parameters**: 400M 📊
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* **Training Data**: Curated Italian text corpus (books, articles, web content) 📚
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* **Model Size**: ~800MB 💾
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Despite its compact size, Alireo-400M demonstrates impressive performance:
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* **Language Understanding**: Maintains high accuracy in Italian language understanding tasks 🎯
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* **Speed**: Efficient inference speed due to optimized architecture ⚡
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* Limited context window compared to larger models
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* May struggle with highly specialized technical content
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* Performance may vary on dialectal variations
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* Not suitable for multilingual tasks
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* **Minimum RAM**: 2GB
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* **Recommended RAM**: 4GB
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* **GPU**: Optional, but recommended for faster inference
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* **Disk Space**: ~1GB (including model and dependencies)
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```bibtex
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@software{alireo2024,
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</p>
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<h2 style="font-size: 32px; text-align: center;">Alireo-400M 🤖 🇮🇹</h2>
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<p style="font-size: 21px; text-align: center;">A Lightweight Italian Language Model</p>
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<h3 style="font-size: 21px; color: #2980b9;">Model Description 📝</h3>
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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.
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<h3 style="font-size: 21px; color: #2980b9;">Key Features ✨</h3>
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* **Architecture**: Transformer-based language model 🏗️
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* **Parameters**: 400M 📊
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* **Training Data**: Curated Italian text corpus (books, articles, web content) 📚
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* **Model Size**: ~800MB 💾
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<h3 style="font-size: 21px; color: #2980b9;">Performance 📈</h3>
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Despite its compact size, Alireo-400M demonstrates impressive performance:
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* **Language Understanding**: Maintains high accuracy in Italian language understanding tasks 🎯
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* **Speed**: Efficient inference speed due to optimized architecture ⚡
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<h3 style="font-size: 21px; color: #2980b9;">Limitations ⚠️</h3>
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* Limited context window compared to larger models
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* May struggle with highly specialized technical content
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* Performance may vary on dialectal variations
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* Not suitable for multilingual tasks
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<h3 style="font-size: 21px; color: #2980b9;">Hardware Requirements 💻</h3>
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* **Minimum RAM**: 2GB
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* **Recommended RAM**: 4GB
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* **GPU**: Optional, but recommended for faster inference
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* **Disk Space**: ~1GB (including model and dependencies)
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<h3 style="font-size: 21px; color: #2980b9;">Citation 📄</h3>
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```bibtex
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@software{alireo2024,
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