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:
- cbf469ce99981cc6dc62c9773aceb0533e4eb6af7ef4208f5620ea9f3dedc350
- Size of remote file:
- 282 kB
- SHA256:
- 376915e019a91e29a61c6da6a44bf4ee9502f07ade075a7489045c545ecc26f4
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