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:
- 65910056d0d7b2f94d918c7535f0b3c759d471717a5ad1523de8e4987057e899
- Size of remote file:
- 1.22 GB
- SHA256:
- 99194d8683531fb43b6bc40954673e52ca6233cf4a12d08d63436d1f6897ce78
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