Instructions to use hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling with Transformers:
# Load model directly from transformers import AutoImageProcessor, FocalNetForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling") model = FocalNetForMaskedImageModeling.from_pretrained("hf-internal-testing/tiny-random-FocalNetForMaskedImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 024b94bf33355cd82aee4d8dd0a05b8a7eb52e387ed9ed474668e1bec9a864c5
- Size of remote file:
- 353 kB
- SHA256:
- 9bb559db265f66a615e7cff05f98ffbb091a59092f114e6e677c10b3954d9f99
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