(from the original "Attention is All You Need" paper) are a classic choice:
[ P(w_1, w_2, ..., w_n) = \prod_i=1^n P(w_i | w_1, ..., w_i-1) ] build a large language model %28from scratch%29 pdf
The decoder architecture is responsible for generating output text based on the encoder's representation. The decoder typically consists of a stack of layers, each of which applies a transformation to the output embeddings. (from the original "Attention is All You Need"
: Implementing Byte Pair Encoding (BPE) and data sampling with a sliding window. Coding Attention w_n) = \prod_i=1^n P(w_i | w_1