Instructions to use WinKawaks/vit-tiny-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WinKawaks/vit-tiny-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="WinKawaks/vit-tiny-patch16-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("WinKawaks/vit-tiny-patch16-224") model = AutoModelForImageClassification.from_pretrained("WinKawaks/vit-tiny-patch16-224") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 160 Bytes
fd78e4f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"do_normalize": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"size": 224
}
|