Instructions to use ProbeX/Model-J__SupViT__model_idx_0639 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0639 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0639") 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("ProbeX/Model-J__SupViT__model_idx_0639") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0639") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a82697182524206616c7cb619d24c5df9c2e29fd5970f303cc746d7fff05c2ad
- Size of remote file:
- 5.37 kB
- SHA256:
- e8e80e3c7e41869de7ea47af081d695e823adcfbf60d6e3701b3f5e1ea8f94da
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