Update README.md

README.md

@@ -63,14 +63,10 @@ from torch import nn
 import torchaudio.transforms as T
 from datasets import load_dataset
 
-
-
-
-commit_hash='b74e8bdecaa1aa58bbd1fd752a7db0695194d9bb'# this is recommended for security reason, the hash might be updated
 # loading our model weights
-model = AutoModel.from_pretrained("m-a-p/MERT-v1-330M", trust_remote_code=True, revision=commit_hash)
+model = AutoModel.from_pretrained("m-a-p/MERT-v1-330M", trust_remote_code=True)
 # loading the corresponding preprocessor config
-processor = Wav2Vec2FeatureExtractor.from_pretrained("m-a-p/MERT-v1-330M",trust_remote_code=True, revision=commit_hash)
+processor = Wav2Vec2FeatureExtractor.from_pretrained("m-a-p/MERT-v1-330M",trust_remote_code=True)
 
 # load demo audio and set processor
 dataset = load_dataset("hf-internal-testing/librispeech_asr_demo", "clean", split="validation")