Instructions to use ppak10/test_ViT-Masked_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppak10/test_ViT-Masked_5 with Transformers:
# Load model directly from transformers import AutoImageProcessor, ViTForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("ppak10/test_ViT-Masked_5") model = ViTForMaskedImageModeling.from_pretrained("ppak10/test_ViT-Masked_5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 392c5451c3c603bbf01f410565e15c841f2063eb9f797669dc91375c2f2daf08
- Size of remote file:
- 4.54 kB
- SHA256:
- 0942d68f90d6569eea9def5463bf1355978cdba23a55c8aa7a19449584d203d3
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