What are Large Language Models?
What are Large Language Models? | NVIDIA Glossary
“Large language models largely represent a class of deep learning architectures called transformer networks. A transformer model is a neural network that learns context and meaning by tracking relationships in sequential data, like the words in this sentence.
A transformer is made up of multiple transformer blocks, also known as layers. For example, a transformer has self-attention layers, feed-forward layers, and normalization layers, all working together to decipher input to predict streams of output at inference. The layers can be stacked to make deeper transformers and powerful language models. Transformers were first introduced by Google in the 2017 paper “Attention Is All You Need.”…”