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:
- 56625a698aae5fec72024dea936ddb3399535e73a8f0cb1bfbd862f92dd717c2
- Size of remote file:
- 1.22 GB
- SHA256:
- 15a305dd53d5cebf3568be65b249c8d06a6502f968ecdfeb963dd11b4b5a85ec
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