Instructions to use ProbeX/Model-J__SupViT__model_idx_0489 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_0489 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_0489") 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_0489") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0489") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20bb1b17593306bc001d9b8c4ef1df9e1b42230e90be4f779654ea1cc3a48aca
- Size of remote file:
- 5.37 kB
- SHA256:
- 67a33a93e0fb78f5cabb53a69f8ecaf99a317150fe216f5f66d3c9b2b8617325
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