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")# pip install -U transformers accelerate # 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 pytorch_model.bin from google/vit-base-patch16-224: direct link, hf CLI and curl.
- Browser
- Download file 346 MB
-
https://huggingface.co/google/vit-base-patch16-224/resolve/2ddc9d4e473d7ba52128f0df4723e478fa14fb80/pytorch_model.bin
- Command line
-
hf download hf://google/vit-base-patch16-224@2ddc9d4e473d7ba52128f0df4723e478fa14fb80/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/google/vit-base-patch16-224/resolve/2ddc9d4e473d7ba52128f0df4723e478fa14fb80/pytorch_model.bin
346 MB
- Xet hash:
- 932cd91d828354c94b22739d6561175801a6f9cdc3fee5a94871f80452413705
- Size of remote file:
- 346 MB
- SHA256:
- 5f17067668129d23b52524f90a805e7d9914c276d90a59a13ebe81a09e40ceca
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