Instructions to use ProbeX/Model-J__SupViT__model_idx_0730 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_0730 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_0730") 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_0730") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0730") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af2585102a988d155ab6c3cb77c199b439dee8622a3962617a4ea9226c0abf95
- Size of remote file:
- 5.37 kB
- SHA256:
- c8bc7de20ebead2450de154395ca0704ee2c223ef602cb8e5b43ff801ac36090
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