Update README.md

README.md

@@ -20,16 +20,16 @@ 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 VideoMAEFeatureExtractor, TimesformerForVideoClassification
+from transformers import AutoImageProcessor, TimesformerForVideoClassification
 import numpy as np
 import torch
 
 video = list(np.random.randn(16, 3, 448, 448))
 
-feature_extractor = VideoMAEFeatureExtractor.from_pretrained("MCG-NJU/videomae-base-finetuned-kinetics")
+processor = AutoImageProcessor.from_pretrained("facebook/timesformer-hr-finetuned-k600")
 model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-hr-finetuned-k600")
 
-inputs = feature_extractor(video, return_tensors="pt")
+inputs = processor(images=video, return_tensors="pt")
 
 with torch.no_grad():
   outputs = model(**inputs)