from sentence_transformers import SentenceTransformer

# Load the pre-trained model
model = SentenceTransformer('stsb-mpnet-base-v2')

# Generate Embeddings
sentence1_emb = model.encode(stsb_test['sentence1'], show_progress_bar=True)
sentence2_emb = model.encode(stsb_test['sentence2'], show_progress_bar=True)

# Cosine Similarity
stsb_test['SBERT BiEncoder_cosine_score'] = cos_sim(sentence1_emb, sentence2_emb)