An example apparatus includes at least one processor; and at least one non-transitory memory comprising computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform; learn importance of one or more parameters by using a training dataset; define one or more masks for indicating the importance of the one or more parameters for a model finetuning; share at least one mask of the one or more masks with at least one of an encoder or a decoder; finetune at least one parameter of the one or more parameters based at least on the at least one mask; send or signal one or more weight updates corresponding to the at least one parameter in a bitstream to the decoder.