Instructions to use ProbeX/Model-J__SupViT__model_idx_0817 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_0817 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_0817") 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_0817") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0817") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a942e31cbde32fe3d1593f0d6181c9ae0bf705767af7124ec54169fc9b580464
- Size of remote file:
- 5.37 kB
- SHA256:
- 209062f2b7005cef2195020bb5a884fc1e462782714e3d12f1176d571929b5ce
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