Instructions to use hf-internal-testing/tiny-random-ViTForMaskedImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTForMaskedImageModeling with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, ViTForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ViTForMaskedImageModeling") model = ViTForMaskedImageModeling.from_pretrained("hf-internal-testing/tiny-random-ViTForMaskedImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-ViTForMaskedImageModeling: direct link, hf CLI and curl.
- Browser
- Download file 178 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-ViTForMaskedImageModeling/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ViTForMaskedImageModeling@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-ViTForMaskedImageModeling/resolve/refs%2Fpr%2F1/model.safetensors
178 kB
- Xet hash:
- 1c0908c6ad91bdddd60dbd00e1d94514d4fa419773838e7a03a9f9b0f6927815
- Size of remote file:
- 178 kB
- SHA256:
- 4e84269a84ac050b3fb783deb8753f03f8d59b77be817aaef73558b38d2f605e
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