senetence-transformers

similarity.py

#!pip install sentence-transformers==2.2.0
from sentence_transformers import SentenceTransformer, util
model = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")
#fbInterests func takes 2 arrays which are contain interests of google and fb and returs a similarty dict with accuracy scores
def fbInterests(google, fb):
    sims={}
    for g in google:
        for f in fb :
            g_embedding = model.encode(g)
            f_embedding = model.encode(f)
            tensor = util.pytorch_cos_sim(f_embedding, g_embedding)
            result = tensor.numpy()[0][0]
            sims[g]=[f,result]
    return sims