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:
- 289eb41936f2053bac24f9cee53a571010bc36ff11473c85acd1a2749e2e5237
- Size of remote file:
- 353 kB
- SHA256:
- 4b152b7b6c2aa19670b2ad794c9f147f46ad3c41ffd36bd02529281d453afd97
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