Update README.md

README.md

@@ -42,7 +42,7 @@ tokenizer_for_restoring = T5Tokenizer.from_pretrained('bond005/ruT5-ASR-large')
 model_for_restoring = T5ForConditionalGeneration.from_pretrained('bond005/ruT5-ASR-large')
 config_for_restoring = GenerationConfig.from_pretrained('bond005/ruT5-ASR-large')
 if torch.cuda.is_available():
-    model_for_restoring = model_for_rescoring.cuda()
+    model_for_restoring = model_for_restoring.cuda()
 
 input_examples = [
     'краеугольным камнем любышь алгоритных машиного обучения является преждес его ' \
@@ -57,8 +57,8 @@ input_examples = [
 ]
 
 for idx, val in enumerate(input_examples):
-    restored = restore_text(val, tokenizer_for_rescoring,
-                            config_for_restoring, model_for_rescoring)
+    restored = restore_text(val, tokenizer_for_restoring,
+                            config_for_restoring, model_for_restoring)
     print('==========')
     print(f'Example {idx + 1}')
     print('==========')