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Update README.md

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@@ -20,16 +20,16 @@ You can use the raw model for video classification into one of the 600 possible
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  Here is how to use this model to classify a video:
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  ```python
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- from transformers import VideoMAEFeatureExtractor, TimesformerForVideoClassification
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  import numpy as np
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  import torch
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  video = list(np.random.randn(8, 3, 224, 224))
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- feature_extractor = VideoMAEFeatureExtractor.from_pretrained("MCG-NJU/videomae-base-finetuned-kinetics")
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  model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-base-finetuned-k600")
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- inputs = feature_extractor(video, return_tensors="pt")
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  with torch.no_grad():
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  outputs = model(**inputs)
 
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  Here is how to use this model to classify a video:
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  ```python
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+ from transformers import AutoImageProcessor, TimesformerForVideoClassification
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  import numpy as np
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  import torch
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  video = list(np.random.randn(8, 3, 224, 224))
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+ processor = AutoImageProcessor.from_pretrained("facebook/timesformer-base-finetuned-k600")
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  model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-base-finetuned-k600")
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+ inputs = processor(images=video, return_tensors="pt")
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  with torch.no_grad():
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  outputs = model(**inputs)