Instructions to use MCG-NJU/videomae-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MCG-NJU/videomae-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="MCG-NJU/videomae-large")# Load model directly from transformers import AutoImageProcessor, AutoModelForPreTraining processor = AutoImageProcessor.from_pretrained("MCG-NJU/videomae-large") model = AutoModelForPreTraining.from_pretrained("MCG-NJU/videomae-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c207e496210dcf0febf7ebf749b59915a29e024acfa5ddc0c023322b833733b
- Size of remote file:
- 1.37 GB
- SHA256:
- c7549bea23c22ab1ab0433c2371e7c9060cf93d209ea1894a87c874a99334a60
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