Instructions to use rish13/videomae_4f with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rish13/videomae_4f with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="rish13/videomae_4f")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("rish13/videomae_4f") model = AutoModelForVideoClassification.from_pretrained("rish13/videomae_4f") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7a443e343ff82f9fe6fb00c60f804648f6f90fab60c15ffbc38a86316b6e00a9
- Size of remote file:
- 345 MB
- SHA256:
- f916bb8bd7f50ad4a8938c6021073682601796dc9e19a373d8269a0f6b190eb9
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