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 tf_model.h5 from google/vit-base-patch16-224: direct link, hf CLI and curl.
- Browser
- Download file 347 MB
-
https://huggingface.co/google/vit-base-patch16-224/resolve/2ddc9d4e473d7ba52128f0df4723e478fa14fb80/tf_model.h5
- Command line
-
hf download hf://google/vit-base-patch16-224@2ddc9d4e473d7ba52128f0df4723e478fa14fb80/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/google/vit-base-patch16-224/resolve/2ddc9d4e473d7ba52128f0df4723e478fa14fb80/tf_model.h5
347 MB
- Xet hash:
- 47dd97211485d010d6db7ceeec052b98bbb84b2e4a4e4480c186f2b21f6af838
- Size of remote file:
- 347 MB
- SHA256:
- 30f9125423060139b80ddae09daa8a1b612eb1eda8fc34a0b58cdfe920cbbc0f
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