Instructions to use ProbeX/Model-J__SupViT__model_idx_0012 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_0012 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_0012") 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_0012") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0012", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9160982aba3b3ef54bc8f9e22a8c0927c77f7e5c1843eab6ab00b84b1c46c0c3
- Size of remote file:
- 5.37 kB
- SHA256:
- 6f36c015d9fc7d051d103a7c73a62ff5d02cb2e5e7ac0693cb280264e0fddece
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