Instructions to use ProbeX/Model-J__SupViT__model_idx_0516 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_0516 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_0516") 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_0516") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0516") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3811605a6b909dc933e8ee77bd96559a5f881a894d1d3c65f80a137e99f97e2
- Size of remote file:
- 5.37 kB
- SHA256:
- 2638b18d1262eca54fa55a90801adcc0d78cdf8700b52dda56fc86a058b7159e
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