Instructions to use ProbeX/Model-J__SupViT__model_idx_0327 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_0327 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_0327") 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_0327") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0327") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e82cae0950ae7d1df814c425a6d75a5c5505dfb84046ac359119a381c3c00425
- Size of remote file:
- 343 MB
- SHA256:
- c9c5cc7a3390344e0d8292e8d20b5c567b9f84e996c89a904a835cdd99662a0b
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