Instructions to use ProbeX/Model-J__SupViT__model_idx_0129 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_0129 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_0129") 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_0129") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0129", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e64cc28bbc0bee9275cb56cacc69dd57e09ebc365f7d412b8b088e73e64ff020
- Size of remote file:
- 5.37 kB
- SHA256:
- f2f6631bbe86f4af91998f295d60c0ec5fd6fb7c31e4c7e0028a473ad46aac65
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