An embedding is a dense vector of numbers that represents a word, a sentence or a document, so that items with similar meaning have close vectors. It captures semantic similarities that the bag of words ignores, and is used for search, clustering and as input to other models.
Example
vecteur = modele.encode('Comment réinitialiser mon mot de passe ?')