def embed(self, documents, verbose=False):
        """Embed a list of n documents/words into an n-dimensional
        matrix of embeddings.

        Arguments:
            documents: A list of documents or words to be embedded
            verbose: No-op variable that's kept around to keep the API consistent. If you want to get feedback on training times, you should use the sklearn API.

        Returns:
            Document/words embeddings with shape (n, m) with `n` documents/words
            that each have an embeddings size of `m`
        """
        try:
            check_is_fitted(self.pipe)
            embeddings = self.pipe.transform(documents)
        except NotFittedError:
            embeddings = self.pipe.fit_transform(documents)

        return embeddings
Embed a list of n documents/words into an n-dimensional
        matrix of embeddings.

        Arguments:
            documents: A list of documents or words to be embedded
            verbose: No-op variable that's kept around to keep the API consistent. If you want to get feedback on training times, you should use the sklearn API.

        Returns:
            Document/words embeddings with shape (n, m) with `n` documents/words
            that each have an embeddings size of `m`
        
bertopic/backend/_sklearn.py