Instructions to use ProbeX/Model-J__SupViT__model_idx_0427 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_0427 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_0427") 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_0427") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0427", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98e84a85550344c82dc99a6a404a3d985b74ca2c0927dc14e840dc317abf7786
- Size of remote file:
- 5.37 kB
- SHA256:
- d8254982b0c2d39bc765c19e18231fb722dfb7c2eb822cea2e9a53239fafcce3
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