Embedder (or encoder)

This type of Language Model takes a string as input and returns a vector as output. This is known as an embedding. Namely, this is a condensed representation of the input content.
The output vector, indeed, embeds the semantic information of the input text.

Despite being non-human readable, the embedding comes with the advantage of living in a Euclidean geometrical space. The embedding can be seen as a point in a multidimensional space, thus, geometrical operations can be applied to it. For instance, measuring the distance between two points can inform us about the similarity between two sentences.