18 September, 2023 - 08:22 AM
Words are converted into mathematical representations called word embeddings. This process transforms words into vectors of numbers, making it easier for the neural network to work and <!--td {border: 1px solid #cccccc;}br {mso-data-placement:same-cell;}-->click here to read with and understand them. Word embeddings capture semantic relationships between words, such as similarity and context. The transformer architecture introduced the attention mechanism, which allows the model to focus on specific parts of the input data when generating text. This helps the model capture long-range dependencies and context more effectively.