Instructions to use ProbeX/Model-J__SupViT__model_idx_0524 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_0524 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_0524") 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_0524") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0524", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eb7e02e45fb33c0337944f5be73c16fffc611774b78a6cc34bb2e008c921721f
- Size of remote file:
- 5.37 kB
- SHA256:
- 6e6e6f91b50a372cc272509a94fd6565942ec0bfbbed69a005a9e6b0c07b93d9
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