from pretrained on tokenizer

run_speech_recognition_ctc.py

@@ -522,10 +522,11 @@ def main():
     # one local process can concurrently download model & vocab.
 
     # load feature_extractor and tokenizer
-    tokenizer = Wav2Vec2CTCTokenizer(tokenizer_name_or_path, 
-                                     use_auth_token=data_args.use_auth_token,
-                                     **tokenizer_kwargs,
-                                    )
+    tokenizer = Wav2Vec2CTCTokenizer.from_pretrained(
+        tokenizer_name_or_path, 
+        use_auth_token=data_args.use_auth_token,
+        **tokenizer_kwargs,
+    )
     feature_extractor = AutoFeatureExtractor.from_pretrained(
         model_args.model_name_or_path, cache_dir=model_args.cache_dir, use_auth_token=data_args.use_auth_token
     )