Instructions to use ProbeX/Model-J__SupViT__model_idx_0974 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_0974 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_0974") 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_0974") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0974") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9783bd3dc77336ed8f3808d22fe5c2d239499ef506c644c032173796d1136d97
- Size of remote file:
- 5.37 kB
- SHA256:
- 08b7c660b6dd99a241a9486ce14e15a647baec32aa4938e159762145427d7076
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