Instructions to use ProbeX/Model-J__SupViT__model_idx_0797 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_0797 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_0797") 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_0797") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0797") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efa70b55d8c3c1f0cf7393badcfdc8cbe330e6fe2025bb65c3dd2fd1dc5746ef
- Size of remote file:
- 5.37 kB
- SHA256:
- 4f479a0e68a02ab69de31f59c75476840bfeff21034e11cc79a4b162c9cd0729
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