How to get a similarity vector from two vectors?
If I understand your question correctly, you have 2 sentences and you converted those sentences into 2 vectors, you want to know how those sentences are similar.
If this is the case use cosine similarity between 2 sentences and cosine similarity is a scalar not a vector its the dot product of your 2 embedding vectors.

from numpy import dot
from numpy.linalg import norm

cos_sim = dot(a, b)/(norm(a)*norm(b))


where a and b are your vectors.

There is direct formula as well:

from sklearn.metrics.pairwise import cosine_similarity

cosine_similarity(vector1,vector2)