Instructions to use rish13/80videomae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rish13/80videomae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="rish13/80videomae")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("rish13/80videomae") model = AutoModelForVideoClassification.from_pretrained("rish13/80videomae") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 798c69a5cf9b4bd062630504bd8b8a3251f30907ba84ba868512ff963a0b46a4
- Size of remote file:
- 345 MB
- SHA256:
- de89473006ec06c7b259da112a782861982a11f177080db3062f9a61d95e8df3
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