Instructions to use hf-internal-testing/tiny-random-SwinForMaskedImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwinForMaskedImageModeling with Transformers:
# Load model directly from transformers import AutoImageProcessor, SwinForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SwinForMaskedImageModeling") model = SwinForMaskedImageModeling.from_pretrained("hf-internal-testing/tiny-random-SwinForMaskedImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53bea83f89d9cb7b6874ae9c86d82498320d66b64cf1f0a08dc2fda053eb5e99
- Size of remote file:
- 316 kB
- SHA256:
- 75ba237d0c5259a1dce332f9c47f7d5355bf405cf0a9a7002dd8efeb01d42ef4
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