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:
- ae2b76c038d0a05f9b8551c73636a215825156822a08954bcae9b6a3fcdd55a5
- Size of remote file:
- 353 kB
- SHA256:
- a00b808e544458201e8984155ec156951f07136ab837e130f6958e8351fa67c1
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