Instructions to use venuv62/vit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use venuv62/vit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="venuv62/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("venuv62/vit-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("venuv62/vit-base-patch16-224") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
pytorch_model.bin
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runs/Oct31_19-29-24_3aa33c176053/events.out.tfevents.1667244571.3aa33c176053.70.3
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