Instructions to use hf-tiny-model-private/tiny-random-ViTForMaskedImageModeling 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-ViTForMaskedImageModeling with Transformers:
# Load model directly from transformers import AutoImageProcessor, ViTForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ViTForMaskedImageModeling") model = ViTForMaskedImageModeling.from_pretrained("hf-tiny-model-private/tiny-random-ViTForMaskedImageModeling") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ad605cfdc1b8c5a9fbb4b8906d04d2d01c45e54f2276b72cfda268072266cde
- Size of remote file:
- 197 kB
- SHA256:
- e7e1027f1f3b8ead4d49b54eac7b3013e66bb351c7c28f3d67ba8861e363c462
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