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
File size: 246 Bytes
27840f8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"crop_size": 30,
"do_normalize": true,
"do_resize": true,
"feature_extractor_type": "ViTFeatureExtractor",
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"resample": 2,
"size": 30
}
|