fix code snippet in model card (#2)

- fix code snippet in model card (b0d8688ea485cafceaa5233f8018a3d067b29b36)
- Update README.md (0dca5362a3365155b15753a58c70150a55c5d0cd)


Co-authored-by: Fatih <fcakyon@users.noreply.huggingface.co>

README.md

@@ -20,16 +20,16 @@ You can use the raw model for video classification into one of the 400 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))
+video = list(np.random.randn(16, 3, 448, 448))
 
-feature_extractor = TimesformerFeatureExtractor.from_pretrained("facebook/timesformer-hr-finetuned-k400")
+processor = AutoImageProcessor.from_pretrained("facebook/timesformer-hr-finetuned-k400")
 model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-hr-finetuned-k400")
 
-inputs = feature_extractor(video, return_tensors="pt")
+inputs = processor(images=video, return_tensors="pt")
 
 with torch.no_grad():
   outputs = model(**inputs)