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:
- 09b998ea80400eb422a0c033298fc893315c8595d2158873ec174d5027c45e89
- Size of remote file:
- 353 MB
- SHA256:
- 46ad483c57f427771665b9527ec8e943015153ae9700543b5b4ef131cd3583ad
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