Instructions to use ProbeX/Model-J__SupViT__model_idx_0821 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_0821 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_0821") 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_0821") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0821", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 192d21fbf74eb6ab5bcf3d3c67b4c2f15490dfe8e5b35c348f3adb2154339c7c
- Size of remote file:
- 5.37 kB
- SHA256:
- 1b5e2bc483300d6c55c57be19a3fb01eca2c6866bfd50c3a03254560008f87da
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