Instructions to use liangy2/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liangy2/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="liangy2/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("liangy2/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("liangy2/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dca17a45a9746b4cf1223cca24c0dd331a006d3c53ceec118acdfefe1b80c46
- Size of remote file:
- 3.38 kB
- SHA256:
- 704aaeb7a0640b8090cf78b1ec59e5ecebf7b982da8b6b7d19735bfc196b450a
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