Sentence transformer to embedding a sentence by using BERT.

You can install it using pip:

pip install -U sentence-transformers

from sentence_transformers import SentenceTransformer
model = SentenceTransformer('all-MiniLM-L6-v2')

#The sentence we like to encode
sentences = ['I love New York and california']

#Sentence is encoded by calling model.encode()
embeddings = model.encode(sentences)

#Print the embedding
for sentence, embedding in zip(sentences, embeddings):
    print("Sentence:", sentence)
    print("Embedding:", embedding)
    print("")

Result:

Sentence: I love New York and california
Embedding: [ 1.37644410e-01 -7.51644969e-02  8.78048167e-02  2.01561265e-02
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 -5.23725212e-05  1.40432995e-02 -7.70160696e-03 -4.15769704e-02
  2.27416754e-02  7.22652897e-02  1.36604654e-02 -2.68634167e-02
 -2.86001954e-02 -9.04295370e-02  2.12521870e-02  1.91395022e-02
  1.73619073e-02 -3.37615646e-02 -6.35999590e-02  5.02365679e-02
  5.41934781e-02  6.28829002e-03  3.82309668e-02  4.64837290e-02
 -3.71122882e-02  1.85275171e-02  1.03333062e-02  4.16899174e-02
 -6.59276778e-03  1.59689356e-02  5.19296229e-02  5.80011085e-02
  7.29451329e-02  2.13103406e-02  3.92759293e-02  5.72733618e-02
  1.19732996e-03  7.22848251e-02  5.61710186e-02  7.10910186e-02
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  2.10559573e-02  8.42723344e-03  9.56717879e-03 -2.08640955e-02
  1.95479728e-02  5.08078672e-02  2.33498700e-02 -4.61519659e-02
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  2.56228428e-02 -4.46879268e-02  2.82586869e-02 -8.13086852e-02
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