Instructions to use rapadilla/videomae-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rapadilla/videomae-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="rapadilla/videomae-base")# Load model directly from transformers import AutoImageProcessor, AutoModelForPreTraining processor = AutoImageProcessor.from_pretrained("rapadilla/videomae-base") model = AutoModelForPreTraining.from_pretrained("rapadilla/videomae-base") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:bc053ca2840a038b1068269a4eec06ca569689e9a1ed9376a5b2b8a111be5290
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size 376873760
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