import gensim
from gensim.models import Word2Vec

data = [['I', 'love', 'dogs'], ['I', 'hate', 'cats'], ['Dogs', 'are', 'cute']]

# Create a Word2Vec model
model = Word2Vec(data, min_count=1)  

# Obtain the word embedding for 'dogs'
word_embedding = model.wv['dogs']

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