Instructions to use google/vit-large-patch16-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-large-patch16-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-large-patch16-384") 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-patch16-384") model = AutoModelForImageClassification.from_pretrained("google/vit-large-patch16-384") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e010f78725227dded0538c7401b9262246434fbb618b9231f0108484382061f
- Size of remote file:
- 1.22 GB
- SHA256:
- e4dc3ea229b52b5da937009baa350b6b04b83d1c435a6d221115994d7fdb9908
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