Update README.md

README.md

@@ -34,10 +34,9 @@ with torch.no_grad():
 
 # Convert embeddings to numpy and normalize
 embeddings = torch.cat(embeddings, dim=0).numpy()
-embeddings_normalized = normalize(embeddings)
 
 # Calculate cosine similarity
-similarity_matrix = cosine_similarity(embeddings_normalized)
+similarity_matrix = cosine_similarity(embeddings)
 
 # Print similarity scores
 print("Similarità tra la sentenza 1 e 2:", similarity_matrix[0, 1])