Instructions to use ProbeX/Model-J__SupViT__model_idx_0721 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_0721 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_0721") 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_0721") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0721", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f391272020f675f801548fb9135208408044a2d1094b2d8ca2e6d52da9a89a87
- Size of remote file:
- 5.37 kB
- SHA256:
- 09eb5f441206fdc0d9a0a99b7d795f96e821ae24038262756fc5036525e5d8f6
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