Instructions to use ProbeX/Model-J__SupViT__model_idx_0031 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_0031 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_0031") 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_0031") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0031") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b53671cffcbc5b8d9de1edfa433ea755ef4fba7d959d3fcfe7bc7bb42fbef10
- Size of remote file:
- 5.37 kB
- SHA256:
- f8c89a440013f35df2a0f50881a823c708413066bb38b0009c9dcd816bfcd0f6
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