Transformer model is a neural network architecture that processes sequential data using self-attention mechanisms instead of recurrent or convolutional operations. Introduced in Vaswani et al.’s 2017 paper “Attention Is All You Need”, it handles input tokens in parallel while maintaining sequence relationships through positional encodings and multi-head attention layers. The architecture’s flexible encoder-decoder framework has