The architecture as a whole is referred to as a transformer (autoregressive decoder-only architecture in the case of gpt style LLMs).

Note that there can be other types of LLMs too that are not necessarily transformer based (SSM, RNN, etc)

Normally, the LLM is composed of multiple transformer blocks, where each block consists of the (mutli-head) attention and fully-connected feedforward components. These are then stacked on top of each other to give the final output of the network.