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timesformer-base-finetuned-k600
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fix code snippet in model card (#3) 

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


Co-authored-by: Fatih <fcakyon@users.noreply.huggingface.co>
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Niels Rogge 2022-12-06 08:15:11 +00:00 committed by system
parent 3da1913755
commit df9bcb190c
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@ -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)