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Model: DeepMount00/Alireo-400m-instruct-v0.1
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+language:
+- it
+- en
+pipeline_tag: text-generation
+datasets:
+- DeepMount00/o1-ITA-REASONING
+- DeepMount00/GPT-4o-ITA-INSTRUCT
+- DeepMount00/Sonnet-3.5-ITA-INSTRUCT
+- DeepMount00/open-perfectblend-ita
+- HuggingFaceTB/cosmopedia
+- DeepMount00/pretraining_multi
+---
+
+---
+
+**💡 Found this resource helpful?** Creating and maintaining open source AI models and datasets requires significant computational resources. If this work has been valuable to you, consider [supporting my research](https://buymeacoffee.com/michele.montebovi) to help me continue building tools that benefit the entire AI community. Every contribution directly funds more open source innovation! ☕
+
+---
+
+<p align="center">
+  <img src="alireo.webp" style="width: 500px; height:500px;"/>
+</p>
+
+<h2 style="font-size: 32px; text-align: center;">Alireo-400M 🤖 🇮🇹</h2>
+<p style="font-size: 21px; text-align: center;">A Lightweight Italian Language Model</p>
+
+<h3 style="font-size: 21px; color: #2980b9;">Model Description 📝</h3>
+
+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.
+
+<h3 style="font-size: 21px; color: #2980b9;">Key Features ✨</h3>
+
+* **Architecture**: Transformer-based language model 🏗️
+* **Parameters**: 400M 📊
+* **Context Window**: 8K tokens 🪟
+* **Training Data**: Curated Italian text corpus (books, articles, web content) 📚
+* **Model Size**: ~800MB 💾
+
+<h3 style="font-size: 21px; color: #2980b9;">Performance 📈</h3>
+
+Despite its compact size, Alireo-400M demonstrates impressive performance:
+
+* **Benchmark Results**: Outperforms Qwen 0.5B across multiple benchmarks 🏆
+* **Language Understanding**: Maintains high accuracy in Italian language understanding tasks 🎯
+* **Speed**: Efficient inference speed due to optimized architecture ⚡
+
+<h3 style="font-size: 21px; color: #2980b9;">Limitations ⚠️</h3>
+
+* 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
+
+<h3 style="font-size: 21px; color: #2980b9;">Hardware Requirements 💻</h3>
+
+* **Minimum RAM**: 2GB
+* **Recommended RAM**: 4GB
+* **GPU**: Optional, but recommended for faster inference
+* **Disk Space**: ~1GB (including model and dependencies)
+
+<h3 style="font-size: 21px; color: #2980b9;">Citation 📄</h3>
+
+```bibtex
+@software{alireo2024,
+  author = {[Michele Montebovi]},
+  title = {Alireo-400M: A Lightweight Italian Language Model},
+  year = {2024},
+}
+```

config.json

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+{
+  "_name_or_path": "/home/michele/PycharmProjects/unsloth_trainer/alireo/checkpoint-3600",
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 51203,
+  "eos_token_id": 51204,
+  "hidden_act": "silu",
+  "hidden_size": 896,
+  "initializer_range": 0.02,
+  "intermediate_size": 4864,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 24,
+  "model_type": "qwen2",
+  "num_attention_heads": 14,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 2,
+  "pad_token_id": 51204,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.47.0",
+  "use_cache": false,
+  "use_mrope": false,
+  "use_sliding_window": false,
+  "vocab_size": 51205
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 51203,
+  "eos_token_id": 51204,
+  "pad_token_id": 51204,
+  "transformers_version": "4.47.0",
+  "repetition_penalty": 1.1
+}

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+size 807587872

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "bos_token": {
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+    "normalized": false,
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+    "single_word": false
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+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+  "add_eos_token": true,
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+  "added_tokens_decoder": {
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+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "bos_token": "<|im_start|>",
+  "chat_template": "{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system\nSei un assistente utile.<|im_end|>\n' }}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "extra_special_tokens": {},
+  "legacy": true,
+  "model_max_length": 4096,
+  "pad_token": "<|im_end|>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false,
+  "vocab_size": 51200
+}