library_name: transformers
datasets:
- telodigoensergio/lc-gpt3.5
language:
- es
Model Card for Model ID
Este modelo es el primer paso hacia un modelo de lenguaje que pueda usarse para reescribir de textos de carácter adminsitrativo con el objetivo de mejorar su comprensión para personas con alto y bajo nivel cultural y socieconómico.
Model Details
Model Description
El modelo es el resultado de un proceso de ajuste fino de phi-2, desarrollado por microsoft con unos 2.5b de parámetros. Para el ajuste se han extraído multitud de textos de índole administrativa de las principales páginas web de la administración del Estado español.
Para la carga y ajuste del modelo se han utilizado técnicas de cuantización con la siguiente configuración:
''' bnb_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type='nf4', bnb_4bit_compute_dtype='float16', bnb_4bit_use_double_quant=True)
'''
y se ha aplicado LoRA a las capas lineales para el fine-tunning.
Prompting
El prompt para el uso sigue la siguiente estructura:
prompt = f"""###System: Lee el siguiente texto y hazlo más claro: ###Texto:
{texto}
###Texto aclarado: """
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Training Details
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Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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