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:
- 7bb8616278b713aa5f0c55384782af4204ce949aa11e53cb2c9dbccd07dff505
- Size of remote file:
- 353 kB
- SHA256:
- 081dca258151362500327bf9b4fcb0498f130a57512e8eea6af9d1cb4b85d067
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