Instructions to use ProbeX/Model-J__SupViT__model_idx_0564 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_0564 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_0564") 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_0564") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0564", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a15f1f8a253978d6a564796f5dd47b3483d5b45c80c2bf005a7291eca7e5f7c7
- Size of remote file:
- 5.37 kB
- SHA256:
- 4b0a99af87eaaaa34d9f06e4121b98f5a0e9d57c1b39b307c49cf6b8e9cdd343
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