Instructions to use hf-tiny-model-private/tiny-random-MaskFormerForInstanceSegmentation 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-MaskFormerForInstanceSegmentation with Transformers:
# Load model directly from transformers import AutoImageProcessor, MaskFormerForInstanceSegmentation processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MaskFormerForInstanceSegmentation") model = MaskFormerForInstanceSegmentation.from_pretrained("hf-tiny-model-private/tiny-random-MaskFormerForInstanceSegmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0dd26a406fbacc0f3bf76bf736509ebab3059803cf6b09abf24221160b938613
- Size of remote file:
- 45.8 MB
- SHA256:
- 308097aaeca84570e83e7119eba937c142f156ec6ca0190b7af788c0a47c4e8f
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