fix code snippet in model card (#3)

- fix code snippet in model card (18f67186e115131c4df8d89788d8d3356da506aa)
- Update README.md (595e15554a3c0eafb01c367e9ef0016658f7655a)


Co-authored-by: Fatih <[email protected]>

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 TimesformerFeatureExtractor, TimesformerForVideoClassification
+from transformers import AutoImageProcessor, TimesformerForVideoClassification
 import numpy as np
 import torch
 
 video = list(np.random.randn(8, 3, 224, 224))
 
-feature_extractor = TimesformerFeatureExtractor.from_pretrained("facebook/timesformer-base-finetuned-k600")
+processor = AutoImageProcessor.from_pretrained("facebook/timesformer-base-finetuned-k600")
 model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-base-finetuned-k600")
 
-inputs = feature_extractor(video, return_tensors="pt")
+inputs = processor(images=video, return_tensors="pt")
 
 with torch.no_grad():
   outputs = model(**inputs)