Instructions to use ProbeX/Model-J__SupViT__model_idx_0675 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_0675 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_0675") 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_0675") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0675") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b2d90a995a23ae4744e8f856a0b7b7c36a40799582f2ce145b56049d095c072
- Size of remote file:
- 5.37 kB
- SHA256:
- f069cdcf0b8c572c9f80ff44e5db918aec450d18fa8f9a380c76f1b44793db84
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