Instructions to use ProbeX/Model-J__SupViT__model_idx_0745 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_0745 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_0745") 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_0745") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0745", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed1cc9d376975455da14ee3c7bd98a3d006f7f71dba596cdb49b42c7d6411583
- Size of remote file:
- 5.37 kB
- SHA256:
- 61db2d2a90975b931d892bf4362444de8bd8061dfb2aac18be2dd578d3125f31
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