Instructions to use danbrooks/videomae-base-finetuned-ucf101-subset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danbrooks/videomae-base-finetuned-ucf101-subset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="danbrooks/videomae-base-finetuned-ucf101-subset")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("danbrooks/videomae-base-finetuned-ucf101-subset") model = AutoModelForVideoClassification.from_pretrained("danbrooks/videomae-base-finetuned-ucf101-subset") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4aaf33ef62f22b6bb5b91a061ed9a67a766f84d405a1a129f34ab095cb778ea
- Size of remote file:
- 345 MB
- SHA256:
- 1022e60e0f20d5b4b7856f033f0f9cc5ed3cdffa0490d09d0df4683b38bafdb1
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