Instructions to use ProbeX/Model-J__SupViT__model_idx_0160 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_0160 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_0160") 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_0160") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0160", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44dcaa89b34310f6c7abcd7bb1abe3e8d69a8962c88a724bb41a91e3e117fc33
- Size of remote file:
- 5.37 kB
- SHA256:
- f01cf44f5794cac4cc8d847f00374148f3a1ff45db3e179b54d253aadaf2a8c0
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