Instructions to use google/vit-base-patch32-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-base-patch32-384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-base-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-base-patch32-384") model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch32-384") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b96015e73729d1b5a06017752a94c2a9f03c85ffc4260b95f058ae3319b502aa
- Size of remote file:
- 353 MB
- SHA256:
- 4fe1af6dd578f86c01a2b47de71c9822bb197ab959f1be6dd1e9f3c6b9139485
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