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README.md
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---
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language: es
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license: apache-2.0
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tags:
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- text-generation
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- transformer
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- pytorch
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---
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# MTP Mini - Modelo de Lenguaje
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Modelo transformer entrenado con las siguientes características:
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## Arquitectura
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- **Parámetros**: ~35.6M
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- **Vocabulario**: 4000 tokens
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- **Capas**: 8
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- **Dimensión**: 512
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- **Cabezas de atención**: 8
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## Mejoras implementadas
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- ✅ RoPE (Rotary Position Embedding)
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- ✅ RMSNorm
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- ✅ SwiGLU activation
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- ✅ Label smoothing
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- ✅ Repetition penalty
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- ✅ Early stopping
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- ✅ Length control
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## Uso
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```python
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import torch
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import pickle
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# Cargar modelo
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with open('mtp_mini.pkl', 'rb') as f:
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model_data = pickle.load(f)
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# Cargar tokenizer
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from tokenizer import MTPTokenizer
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tokenizer = MTPTokenizer('mtp_tokenizer.model')
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# Cargar modelo
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from model import MTPMiniModel
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model = MTPMiniModel(**model_data['config']['model'])
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model.load_state_dict(model_data['model_state_dict'])
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model.eval()
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# Generar texto
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prompt = "¿Qué es la inteligencia artificial?"
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input_ids = torch.tensor([tokenizer.encode(prompt)])
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output = model.generate(input_ids, max_new_tokens=100)
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print(tokenizer.decode(output[0].tolist()))
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```
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## Entrenamiento
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- Dataset: Corpus personalizado en español
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- Épocas: 0
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- Mejor val loss: 5.1245
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Entrenado en Google Colab.
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