Instructions to use ProbeX/Model-J__SupViT__model_idx_0445 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_0445 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_0445") 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_0445") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0445") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3dc8ec0cbadde165c0a84409138ac329b7ee22fe0aa30aa72f32955fc9445f6e
- Size of remote file:
- 5.37 kB
- SHA256:
- 0e14ba7a6c6671f34dc0f256aec9eba6b224e35f496c6660e02bdcbd2980464a
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