Vector embedding is a way to represent data as a matrix of numbers in a high-dimensional space. This allows your model to understand the data, its meaning, and the relationships between different pieces of data.
In relation to text generation, text is converted into vector embeddings, where each word is represented as a point in a high-dimensional space. For example, words with similar meanings such as “cat” and “dog” have similar vector representations for a house pet.