Instructions to use hf-tiny-model-private/tiny-random-TimesformerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-TimesformerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-TimesformerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-TimesformerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-TimesformerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1695d190e17bc5e487afb00ab23a790162ebc377fd643759cacc1c2ee9b5d0a8
- Size of remote file:
- 260 kB
- SHA256:
- 6e2cbfad03def3d161e183b467037d33cce1afca702d574a00959994e89109b5
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