Create app.py

app.py

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+from sentence_transformers import SentenceTransformer, util
+model = SentenceTransformer('all-MiniLM-L6-v2')
+
+# Two lists of sentences
+sentences1 = ['The cat sits outside',
+             'A man is playing guitar',
+             'The new movie is awesome']
+
+sentences2 = ['The dog plays in the garden',
+              'A woman watches TV',
+              'The new movie is so great']
+
+#Compute embedding for both lists
+embeddings1 = model.encode(sentences1, convert_to_tensor=True)
+embeddings2 = model.encode(sentences2, convert_to_tensor=True)
+
+#Compute cosine-similarities
+cosine_scores = util.cos_sim(embeddings1, embeddings2)
+
+#Output the pairs with their score
+for i in range(len(sentences1)):
+    print("{} \t\t {} \t\t Score: {:.4f}".format(sentences1[i], sentences2[i], cosine_scores[i][i]))