Update README.md

README.md

@@ -10,9 +10,11 @@ model = AutoModelForSequenceClassification.from_pretrained('dmrau/bow-bert')
 tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
 
 # tokenize query and passage and concatenate them
-inp = tokenizer(['this is a query'], ['this is a passage'], return_tensors='pt')
-
+inp = tokenizer(['this is a query','query a is this'], ['this is a passage', 'passage a is this'], return_tensors='pt')
 # get estimated score
 print('score', model(**inp).logits[:, 1])
 
+### outputs identical scores for different 
+### word orders as the model is order invariant:
+# [-2.9463, -2.9463]
 ```