Instructions to use ProbeX/Model-J__SupViT__model_idx_0110 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_0110 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_0110") 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_0110") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0110", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19f44d40adb9431cdc0c9a7020708a9a0ee549b43b8a6549781169d7ba22132a
- Size of remote file:
- 5.37 kB
- SHA256:
- 2e33ba9d6d61ca22b7757dd6415f08cb719a1b8889e06f3d3a876b98ec02f0fd
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