Instructions to use hf-tiny-model-private/tiny-random-DeiTForMaskedImageModeling 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-DeiTForMaskedImageModeling with Transformers:
# Load model directly from transformers import AutoImageProcessor, DeiTForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DeiTForMaskedImageModeling") model = DeiTForMaskedImageModeling.from_pretrained("hf-tiny-model-private/tiny-random-DeiTForMaskedImageModeling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2b2f47cd49ff5ed4d07f87be52917c0ddd22344b006dcc6d151b0c00463de43
- Size of remote file:
- 197 kB
- SHA256:
- e1e0f734929cf72ee63ed7094e13e7e492a291911769e6ad97c0c94388668cb5
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