This text explores a structured pruning method for state-of-the-art fashions, that makes use of a GLU structure, enabling the creation of smaller and extra environment friendly massive language fashions.
Disclaimer: This text was initially written in Spanish and translated into English utilizing AI instruments as help to make sure accuracy and consistency. Yow will discover the unique Spanish model here.
As massive language fashions proceed to develop in dimension to attain higher capabilities, the demand for extra environment friendly, smaller variations has develop into extra needed than ever. Nevertheless, lowering a mannequin’s dimension with out dropping its core performance is a fragile balancing act.
Strategies equivalent to quantization and pruning are generally used to lower dimension, whereas strategies like information distillation or switch studying assist retain or recuperate the capabilities misplaced throughout the discount course of.
Amongst these, pruning stands out as one of the crucial efficient methods for lowering mannequin dimension. In contrast to quantization, which simplifies numerical representations, pruning entails eradicating particular elements of the mannequin, equivalent to neurons or total layers. However this effectiveness comes at a value: pruning…