Instructions to use ProbeX/Model-J__SupViT__model_idx_0603 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_0603 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_0603") 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_0603") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0603") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f98daa079fe5497bef08c438a27c41241ef1a7d0c97b28a8d485f32bf4ebddb
- Size of remote file:
- 5.37 kB
- SHA256:
- 4f592d5e77bcf59890a291c8cba47e7af0c65415be125ed7ae19f679c67f88c4
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