Instructions to use ydshieh/tiny-random-ViTForMaskedImageModeling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-ViTForMaskedImageModeling with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, ViTForMaskedImageModeling processor = AutoImageProcessor.from_pretrained("ydshieh/tiny-random-ViTForMaskedImageModeling") model = ViTForMaskedImageModeling.from_pretrained("ydshieh/tiny-random-ViTForMaskedImageModeling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ydshieh/tiny-random-ViTForMaskedImageModeling: direct link, hf CLI and curl.
- Browser
- Download file 196 kB
-
https://huggingface.co/ydshieh/tiny-random-ViTForMaskedImageModeling/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ydshieh/tiny-random-ViTForMaskedImageModeling/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ydshieh/tiny-random-ViTForMaskedImageModeling/resolve/main/pytorch_model.bin
196 kB
- Xet hash:
- a7b5904c496fff5b71585a38f545377d973f2e81273e735dddf1c0f1e827c26a
- Size of remote file:
- 196 kB
- SHA256:
- bcfd08d05fe738b7f86ffe709437cbfabfd42c786f90ff89cc6d0379619737c8
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