Instructions to use ProbeX/Model-J__SupViT__model_idx_0039 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_0039 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_0039") 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_0039") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0039") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89af145a9433b6702359f4e4a8f76fbf125b5edabb10662901b713c283806865
- Size of remote file:
- 5.37 kB
- SHA256:
- ef684631d784a5af7169a66cce0337efcfbfa9da4d89a948c6c9393581ebfcf2
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