docs: fix padding error

README.md

@@ -50,8 +50,9 @@ with torch.no_grad():
         all_sent.append(" ".join(tokenize(sent)).replace("_","[!und:]"))
 
     sentence = " _ ".join(all_sent)
-    token_ids = tokenizer(sentence, return_tensors = 'pt')['input_ids']
-    features = model(token_ids)
+    tokenized_text = tokenizer(sentence, return_tensors = 'pt')
+    token_ids = tokenized_text['input_ids']
+    features = model(**tokenized_text)
 ```
 
 For batch processing,
@@ -69,8 +70,9 @@ with torch.no_grad():
 
         sentence = " _ ".join(all_sent)
         inputList.append(sentence)
-    token_ids = tokenizer(inputList, padding = True, return_tensors = 'pt').input_ids
-    features = model(token_ids)
+    tokenized_text = tokenizer(inputList, padding = True, return_tensors = 'pt')
+    token_ids = tokenized_text['input_ids']
+    features = model(**tokenized_text)
 ```
 
 To use HoogBERTa as an embedding layer, use