Instructions to use ProbeX/Model-J__SupViT__model_idx_0856 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_0856 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_0856") 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_0856") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0856", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e332fbf9428efe221e08f568e387fea2c75052a3e36013c3d6b0ea41a08bae3
- Size of remote file:
- 5.37 kB
- SHA256:
- c0eb1d8e7325f836918c7c8920d0284d5957a2efba1123004d6b7e470df0d7be
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