Instructions to use mmekias/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mmekias/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mmekias/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("mmekias/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("mmekias/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0498a64de4242e65d4c36dc42ff1a1b03051f15212bc7659ea28fd92be265f9f
- Size of remote file:
- 343 MB
- SHA256:
- b89bcab8922707bd9cfbd2809ed22b14726d6f6340068e1e93b5183eac083edb
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