Instructions to use Hugh1111111/exampleVIT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hugh1111111/exampleVIT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hugh1111111/exampleVIT") 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("Hugh1111111/exampleVIT") model = AutoModelForImageClassification.from_pretrained("Hugh1111111/exampleVIT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0bfe36f4e9a4c092e4b2628843f914ef9010a1f069424cb3c4ab14e7e0b06be
- Size of remote file:
- 14.6 kB
- SHA256:
- 08d1f90efd2ec5917f1161087472df1d694f3bfb61fcf103c3c900b90c19e167
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