Instructions to use ProbeX/Model-J__SupViT__model_idx_0972 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_0972 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_0972") 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_0972") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0972") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 69e15b89f701632a90debcadb6ff63196b681cc4c67fc0e65994c41dea013676
- Size of remote file:
- 5.37 kB
- SHA256:
- 570362fbdc6d8ef3b0382b6ba2ea9c03fee994ab1407032d4650758d001c19d5
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