Instructions to use mgoin/vit-base-beans-one-shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgoin/vit-base-beans-one-shot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mgoin/vit-base-beans-one-shot") 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("mgoin/vit-base-beans-one-shot") model = AutoModelForImageClassification.from_pretrained("mgoin/vit-base-beans-one-shot") - Notebooks
- Google Colab
- Kaggle
Upload model.onnx with huggingface_hub
Browse files- model.onnx +3 -0
model.onnx
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version https://git-lfs.github.com/spec/v1
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size 87003889
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