Instructions to use google/vit-large-patch32-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-large-patch32-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-large-patch32-384") 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("google/vit-large-patch32-384") model = AutoModelForImageClassification.from_pretrained("google/vit-large-patch32-384") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f51a03dec2a332d55d64f084bee1bcfd0d346a0c005590d277b7e43c0ca2aca7
- Size of remote file:
- 1.23 GB
- SHA256:
- 1558cf23dedc8c1bd7aed8e20b316e31b54669036dc864cbadb9bf6e5256e613
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