Instructions to use ProbeX/Model-J__SupViT__model_idx_0957 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_0957 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_0957") 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_0957") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0957", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efbfe8d1aff69dd5b378a32221f59b5c02c4b36f0f57a2a66833cfba36bf3e97
- Size of remote file:
- 5.37 kB
- SHA256:
- 3e5cfe355a1395e8896c2c853b29515e61bfc96bbfb31c3d00c9a555b9a53ca4
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