One effective approach for determining semantic similarity between two texts involves utilizing word embeddings along with cosine similarity. The Sentence Transformers Python framework provides transformers which gives state-of-art word embeddings specifically designed for this purpose. Below is an example code:

import sentence_transformers
from sklearn.metrics.pairwise import cosine_similarity
model_name = 'all-mpnet-base-v2'

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