fix a typo in code snippet
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README.md
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@@ -20,13 +20,13 @@ You can use the raw model for video classification into one of the 400 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
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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 =
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model = TimesformerForVideoClassification.from_pretrained("facebook/timesformer-base-finetuned-k400")
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inputs = feature_extractor(video, return_tensors="pt")
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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-k400")
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inputs = feature_extractor(video, return_tensors="pt")
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