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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0dd4ec7f4813ba7de7b9e8d47c409aad236d1d3c9116458f62c5518e5be95595
- Size of remote file:
- 1.22 GB
- SHA256:
- 83512c6448d41d8de6426f52bee5cddb610f23264207f2dfc5c8538c574423f6
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