Update README.md

README.md

@@ -64,11 +64,10 @@ import torchaudio.transforms as T
 from datasets import load_dataset
 
 
-commit_hash='55fa29e5522049926c03d2ff9ae54d22c20e668f'# this is recommended for security reason, the hash might be updated
 # loading our model weights
-model = AutoModel.from_pretrained("m-a-p/MERT-v1-95M", trust_remote_code=True, revision=commit_hash)
+model = AutoModel.from_pretrained("m-a-p/MERT-v1-95M", trust_remote_code=True)
 # loading the corresponding preprocessor config
-processor = Wav2Vec2FeatureExtractor.from_pretrained("m-a-p/MERT-v1-95M",trust_remote_code=True, revision=commit_hash)
+processor = Wav2Vec2FeatureExtractor.from_pretrained("m-a-p/MERT-v1-95M",trust_remote_code=True)
 
 # load demo audio and set processor
 dataset = load_dataset("hf-internal-testing/librispeech_asr_demo", "clean", split="validation")