Instructions to use ProbeX/Model-J__SupViT__model_idx_0250 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_0250 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_0250") 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_0250") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0250") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea7d98efa41d635ed8c268789c193848fbf080e4afbf226cef7cebc53bbb53f9
- Size of remote file:
- 5.37 kB
- SHA256:
- d21e3f2a0780d3554941b3f3028abc97fb8e703105591296de6216635135eb23
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