Instructions to use ProbeX/Model-J__SupViT__model_idx_0887 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_0887 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_0887") 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_0887") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0887") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae8412cb1bf3b8af3b8df5a02436eb8f0d39179d37d5caa6cf39112f68a5b20d
- Size of remote file:
- 5.37 kB
- SHA256:
- db6219a671ba3a3fbfe2fd560e0914ec1debc81256bf6074ca5e04310eb3251b
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