Update README.md

README.md

@@ -69,8 +69,8 @@ Use the entity embeddings to predict the subsumption relationships between them.
 
 ```python
 # suppose we want to compare "personal computer" and "computer", "berry" and "fruit"
-child_entity_embeddings = model.encode(["personal computer", "berry"])
-parent_entity_embeddings = model.encode(["computer", "fruit"])
+child_entity_embeddings = model.encode(["personal computer", "berry"], convert_to_tensor=True)
+parent_entity_embeddings = model.encode(["computer", "fruit"], convert_to_tensor=True)
 
 # compute the hyperbolic distances and norms of entity embeddings
 dists = model.manifold.dist(child_entity_embeddings, parent_entity_embeddings)