Instructions to use ProbeX/Model-J__SupViT__model_idx_0391 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_0391 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_0391") 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_0391") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0391") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1d6df38b85555b4ff21302bc584e095777de9bd4264094b0dc95502ec8247ce
- Size of remote file:
- 5.37 kB
- SHA256:
- 226e81a1ececd03fe095a5205963d7a0c23d67b1e55d76ec95991a19a488e5f2
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