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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (b18261655ef41094d0119f165e1443ab245d5c8e) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>d285164
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Update README.md (#1)
- Update README.md (81acb93945c9afe4c8e47a7c1989feae501ccc0f) Co-authored-by: Pooriya Kh <Pooriya-Kh@users.noreply.huggingface.co>1c7b428
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