What is the role of the embedding layer in transformers?

The embedding layer in transformers converts input tokens (which are typically discrete identifiers) into dense vector representations. These embeddings capture semantic similarities between tokens, allowing the model to process them numerically. The embedding layer is crucial as it provides the initial representation of input data, which is then modified by subsequent transformer layers during processing, helping the model understand context and relationships within the data.