Instructions to use ProbeX/Model-J__SupViT__model_idx_0504 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_0504 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_0504") 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_0504") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0504", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 56998c0e1c83b18ccd5d5ac4065e22d3296c969d1586268ec01aef0c938c94ff
- Size of remote file:
- 5.37 kB
- SHA256:
- c5cd0167f8c3a1dd318ed6e84c67c272bf07615738d5e1246a5dcfcef17b2243
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