Instructions to use ProbeX/Model-J__SupViT__model_idx_0001 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_0001 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_0001") 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_0001") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0001", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34004a84bc3357b5a2543554a0f1b8d1e841462376ff76b781325b6b3c669386
- Size of remote file:
- 5.37 kB
- SHA256:
- 30de9702b834ee11f6bb0bf1f3db9fe2635883f930e38fb39b295c5caeab38ac
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