I've loaded pretrained word2vec embeddings into a python dictionary of the form
{word: vector}
As an example, an element of this dictionary is
w2v_dict["house"] = [1.1,2.0, ... , 0.2]
I would like to load this model into Gensim (or a similar library) so that I can find euclidean distances between embeddings.
I understand that pretrained embeddings typically come in a .bin file which can be loaded into Gensim. But if I only have a dictionary of this form, how would I load the vectors into a model?