fix a typo in code snippet

README.md

@@ -20,13 +20,13 @@ You can use the raw model for video classification into one of the 600 possible
 Here is how to use this model to classify a video:
 
 ```python
-from transformers import TimesformerFeatureExtractor, TimesformerForVideoClassification
+from transformers import VideoMAEFeatureExtractor, TimesformerForVideoClassification
 import numpy as np
 import torch
 
 video = list(np.random.randn(8, 3, 224, 224))
 
-feature_extractor = TimesformerFeatureExtractor.from_pretrained("facebook/timesformer-hr-finetuned-k600")
+feature_extractor = VideoMAEFeatureExtractor.from_pretrained("MCG-NJU/videomae-base-finetuned-kinetics")
 model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-hr-finetuned-k600")
 
 inputs = feature_extractor(video, return_tensors="pt")