Instructions to use rish13/videomae3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rish13/videomae3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="rish13/videomae3")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("rish13/videomae3") model = AutoModelForVideoClassification.from_pretrained("rish13/videomae3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b2ce07b558cc9ca3dd81ce5461c8c643f4da607cb97981772bc7368a2e819b5
- Size of remote file:
- 1.22 GB
- SHA256:
- c4624ea97ac5fc7a9705707cf36c68bc852b5b741766483e657becacd2b75574
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