Instructions to use ProbeX/Model-J__SupViT__model_idx_0916 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_0916 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_0916") 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_0916") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0916") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a378213e4338a4ef77cacc7df73641f718c9ef595af9fa0eb0d4bfb582bb5a74
- Size of remote file:
- 5.37 kB
- SHA256:
- fbcdec741fdb9c79af029b66b3d27101c64ae3b444745205acaaa1a60238b1f8
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