Add sentence similarity

Add example from sentence-transformers

app.py

@@ -4,6 +4,35 @@ dataset = load_dataset("roneneldan/TinyStories")
 
 st.write(dataset['train'][0])
 
+#-------------------------------------------------------------
+#-------------------------------------------------------------
+
+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]))
+
+
+#-------------------------------------------------------------
+#-------------------------------------------------------------
 # ego_graph.py
 # An example of how to plot a node's ego network 
 # (egonet). This indirectly showcases slightly more involved