Instructions to use muneeb1812/videomae-base-fake-video-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muneeb1812/videomae-base-fake-video-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="muneeb1812/videomae-base-fake-video-classification")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("muneeb1812/videomae-base-fake-video-classification") model = AutoModelForVideoClassification.from_pretrained("muneeb1812/videomae-base-fake-video-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44e9248ee857115c58cb61385d358042b5220781ede8fa2db9c9c53c118020aa
- Size of remote file:
- 345 MB
- SHA256:
- 274401d5eaa6701f020cf02e22e24778b27a24c3fdc57074a3a22506837779d7
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