Instructions to use ProbeX/Model-J__SupViT__model_idx_0956 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_0956 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_0956") 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_0956") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0956") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5612e415f925a888911e6cce337856996934d5f438817d12bb23a62baef8ae6c
- Size of remote file:
- 5.37 kB
- SHA256:
- db6d92311942cf2b6db3738c3d149d357bb9345592ae5cf8d8a7f80693600b00
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