Instructions to use ProbeX/Model-J__SupViT__model_idx_0886 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_0886 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_0886") 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_0886") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0886") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dfab6904869ac9459c4f90492994e715bd83844dd1e2d5d30495bcd6bc09fa1a
- Size of remote file:
- 5.37 kB
- SHA256:
- f78f9cbf08256c75e6996ad33c1d82f8ec210183e2f402297756ef4dbf6a510b
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