Instructions to use ProbeX/Model-J__SupViT__model_idx_0333 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_0333 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_0333") 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_0333") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0333", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f549464c30daf2d45f7bec7e2203d33e73cf7b9933d9996740a6958a77f7260a
- Size of remote file:
- 5.37 kB
- SHA256:
- 16873c682ec70abdd4ed6ce0da5328bae4747e63505b99ea8886a2da2ea103be
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