Update README.md

README.md

@@ -55,7 +55,7 @@ You can also use with the ```Auto```API:
 ```
 >>> import torch, librosa
 >>> from transformers import AutoModelForAudioClassification, Wav2Vec2FeatureExtractor
->>> feature_extractor = Wav2Vec2FeatureExtractor(feature_size=1, sampling_rate=16000, padding_value=0.0, do_normalize=True, return_attention_mask=False)
+>>> feature_extractor = Wav2Vec2FeatureExtractor()
 >>> model = AutoModelForAudioClassification.from_pretrained("juliensimon/wav2vec2-conformer-rel-pos-large-finetuned-speech-commands")
 >>> audio, rate = librosa.load("up16k.wav", sr = 16000)
 >>> inputs = feature_extractor(audio, sampling_rate=16000, return_tensors = "pt")