Instructions to use ProbeX/Model-J__SupViT__model_idx_0866 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_0866 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_0866") 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_0866") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0866") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddfde0f8db2a49d59d16b6644a805f0f0bfae6464625cd391b0d3bf9a28a8a27
- Size of remote file:
- 5.37 kB
- SHA256:
- d79558119f67f42182499c8d81d18cf05918b4ed73819f3b14a555f20f0da8c8
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