Instructions to use ProbeX/Model-J__SupViT__model_idx_0363 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_0363 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_0363") 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_0363") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0363") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b65ecd39ee3b86d65f6286500792d8d0aefd5e3de70538094c012fd7f76c33c4
- Size of remote file:
- 5.37 kB
- SHA256:
- d4520c71695cc8b9f1c3aa4d57ec25f8850b4bd6c8a2dd32896f803e72216205
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