Instructions to use Yoonhj/vit-base-beans-demo-v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yoonhj/vit-base-beans-demo-v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Yoonhj/vit-base-beans-demo-v5") 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("Yoonhj/vit-base-beans-demo-v5") model = AutoModelForImageClassification.from_pretrained("Yoonhj/vit-base-beans-demo-v5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3442afa0d00d7f1b83906a5264a148d2d7beedbbc2960ac1f36fef06802d8430
- Size of remote file:
- 5.11 kB
- SHA256:
- 0d1ab365def77f9c96e34b54c1090193e6010632a48305309be00944cd16f2f3
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