Update app.py

app.py

@@ -10,12 +10,17 @@ def load_sbert():
 
 model = load_sbert()
 
+
 def calculate_similarity(word1, word2):
     embeddings1 = model.encode(word1)
     embeddings2 = model.encode(word2)
+
+    # Convert NumPy arrays to tensors
+    embeddings1 = torch.tensor(embeddings1)
+    embeddings2 = torch.tensor(embeddings2)
+
     cos_sim = torch.nn.functional.cosine_similarity(embeddings1, embeddings2, dim=0)
     return cos_sim.item()
-
 # Streamlit interface
 st.title("Word Similarity Checker")