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:
- 8988383f0b54ec4302f573365f14967ea872334b5d7d0dc8ea6d3987744ad256
- Size of remote file:
- 353 kB
- SHA256:
- 5ecedeb0ab91e7c5f978ec702534fd7712dc851f80c221efc824a8532f4ac5f6
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