Instructions to use ProbeX/Model-J__SupViT__model_idx_0941 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_0941 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_0941") 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_0941") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0941") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3184f5158b1b245b87c74b170af38c1356cfac9f09a9e2da3bb4b2c8fad9b3d
- Size of remote file:
- 5.37 kB
- SHA256:
- b7cee3b35f280cf1f05dbde8a7a84ecaec941a7e85879a517d38aac3d88f9fd1
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