Instructions to use fmagot01/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fmagot01/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fmagot01/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("fmagot01/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("fmagot01/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ad86bdf07dcacd40dbb05747f17efa7d8f8e7c085669b1f9ce6fb7085e931ae
- Size of remote file:
- 343 MB
- SHA256:
- b556adbd877d5fbb2f8e4228630a49e6010ec18cc1c59d4002ca28523bb2dbb7
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