This text explores a structured pruning approach for state-of-the-art fashions, that makes use of a GLU structure, enabling the creation of smaller and extra environment friendly giant 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. You will discover the unique Spanish model right here.
As giant language fashions proceed to develop in measurement to attain better capabilities, the demand for extra environment friendly, smaller variations has turn into extra crucial than ever. Nonetheless, lowering a mannequin’s measurement with out shedding its core performance is a fragile balancing act.
Methods resembling quantization and pruning are generally used to lower measurement, whereas strategies like information distillation or switch studying assist retain or get well the capabilities misplaced through the discount course of.
Amongst these, pruning stands out as some of the efficient methods for lowering mannequin measurement. In contrast to quantization, which simplifies numerical representations, pruning includes eradicating particular components of the mannequin, resembling neurons or whole layers. However this effectiveness comes at a price: pruning…