Instructions to use ProbeX/Model-J__SupViT__model_idx_0194 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_0194 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_0194") 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_0194") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0194") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f62e08584d0109373f70608ebac9c1e5c160c44a1751543ce9aefda00fccd145
- Size of remote file:
- 5.37 kB
- SHA256:
- d79126b22bcb34a74b26fd1fa81dd2b290f2ecfc49ee7642adb4a3c8de2cae12
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