Instructions to use prasankumar93/nateraw-vit-base-beans-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prasankumar93/nateraw-vit-base-beans-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prasankumar93/nateraw-vit-base-beans-onnx") 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("prasankumar93/nateraw-vit-base-beans-onnx") model = AutoModelForImageClassification.from_pretrained("prasankumar93/nateraw-vit-base-beans-onnx") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
https://huggingface.co/nateraw/vit-base-beans with ONNX weights
# command for conversion
optimum-cli export onnx --model nateraw/vit-base-beans nateraw-vit-base-beans-onnx/
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