Instructions to use hanyp/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanyp/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hanyp/vit-base-beans", device_map="auto") 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("hanyp/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("hanyp/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 42c072b7f8419707bda7ed36d84c90692b7cab8096de840e4f763bdcca0aed38
- Size of remote file:
- 5.18 kB
- SHA256:
- 7d64c62453989e4d71fd9feb8aa2431fc8a68a8af0c4b53d926f9e3dc3180f34
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