Instructions to use corranm/vit-tiny-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use corranm/vit-tiny-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="corranm/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("corranm/vit-tiny-patch16-224") model = AutoModelForImageClassification.from_pretrained("corranm/vit-tiny-patch16-224") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b5607c8b2a95ff0474d8e74e5323c7ee965cf3ffa350806b0e5cfd83394e0af
- Size of remote file:
- 22.1 MB
- SHA256:
- 555b806e9d76cce985357a73fb5e5407ec87800b3ccbcce89c15dd4e44a931b5
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