Instructions to use ProbeX/Model-J__SupViT__model_idx_0943 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_0943 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_0943") 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_0943") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0943") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35a0bb8b604643faa4a944e2f2e674d612fce57f89de24252a068f56235eabb9
- Size of remote file:
- 5.37 kB
- SHA256:
- 32564eb5522ee83c1c8d02892a2f5c392ba76e76bea56eec28c1d6bcfd40c845
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