Instructions to use ProbeX/Model-J__SupViT__model_idx_0019 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_0019 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_0019") 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_0019") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0019") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 706a5d3c6437e345d26e91df0a1ba736e0ac416aed76d854a5c0d701634d2acb
- Size of remote file:
- 5.37 kB
- SHA256:
- 81774b93b9f162beafa279864834c72adb8024a7335f6324a1670a3861b920be
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