Instructions to use google/vit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/vit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="google/vit-base-patch16-224") 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-patch16-224") model = AutoModelForImageClassification.from_pretrained("google/vit-base-patch16-224", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download .gitattributes from google/vit-base-patch16-224: direct link, hf CLI and curl.
- Browser
- Download file 690 Bytes
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https://huggingface.co/google/vit-base-patch16-224/resolve/db75733ce9ead4ed3dce26ab87a6ed2f6f565985/.gitattributes
- Command line
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hf download hf://google/vit-base-patch16-224@db75733ce9ead4ed3dce26ab87a6ed2f6f565985/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/google/vit-base-patch16-224/resolve/db75733ce9ead4ed3dce26ab87a6ed2f6f565985/.gitattributes
690 Bytes
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