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:
- 9fd39c152a3d77471d8db3499bd0d843280b79e0d1b93c88821ab9b5c23352ef
- Size of remote file:
- 45.7 MB
- SHA256:
- a6796e17b6a06fdf2dec7c0b71821d4e6e21eb589df23ad955602b86f964b8f2
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