chunk_content: eights can be merged with the base model.
  In principle, IA3 can be applied to any subset of weight matrices in a neural network to reduce the number of trainable
  parameters. Following the authors’ implementation, IA3 weights are added to the key, value and feedforward layers
  of a Transformer model. Given the target layers for injecting IA3 parameters, the number of trainable parameters
  can be determined based on the size of the weight matrices.