Recent research has exhibited a compelling trend in the realm of language modeling: scaling laws. These laws highlight a remarkable correlation between model size and performance on a variety of natural language processing tasks. As models grow larger, encompassing millions or even billions of parameters, their capabilities intensify significantly.