Instructions to use yaojiapeng/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yaojiapeng/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="yaojiapeng/vit-base-beans") 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("yaojiapeng/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("yaojiapeng/vit-base-beans") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 598f5c8a508d674e6406d55e95024372b382ec0f0d07dfbbe94e65325fa50e93
- Size of remote file:
- 343 MB
- SHA256:
- 754f46127752ee8d9d2212468801a63230569dc8806b86959d79710738d6d85d
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