Instructions to use hf-internal-testing/tiny-random-DeiTForMaskedImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DeiTForMaskedImageModeling with Transformers:
# Load model directly from transformers import AutoImageProcessor, DeiTForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DeiTForMaskedImageModeling") model = DeiTForMaskedImageModeling.from_pretrained("hf-internal-testing/tiny-random-DeiTForMaskedImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddcfffc45b4fb3236ca9a66fd7d8546f00269a386bc8a8f3ae53dba0900d6cad
- Size of remote file:
- 197 kB
- SHA256:
- cd9172df675ac844b399c0bf3aab8fa0864e29957f1025a9e9e41b0d35ea66f6
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