Instructions to use google/vit-large-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-large-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-large-patch16-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("google/vit-large-patch16-224", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 170d53ce6ab3bf2e30606bc82234d718ce487542cb9ab7793068e7854f8f7a36
- Size of remote file:
- 1.22 GB
- SHA256:
- 69bc0b1734e832067a050c8f73239a22736888330c9ecf9b3ff74a598d2ce1f4
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