Transformer Embeddings

Transformer embeddings refer to the vector representations of input data, such as text or images, generated by transformer models, a type of neural network architecture. These embeddings capture complex patterns and relationships in the data, making them a crucial component in various natural language processing and computer vision tasks, and are widely used in research and applications such as language translation, sentiment analysis, and image classification.