5 Simple Techniques For large language models
Neural network primarily based language models ease the sparsity difficulty by the way they encode inputs. Word embedding layers develop an arbitrary sized vector of every word that incorporates semantic relationships also. These steady vectors develop the Significantly necessary granularity inside the probability distribution of the following word