Instructions to use ProbeX/Model-J__SupViT__model_idx_0396 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_0396 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_0396") 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_0396") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0396") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 859b18f076b29ce22f56183a33ee377c71cc765dbe162c81f7cd60485caf693d
- Size of remote file:
- 5.37 kB
- SHA256:
- dfbcade70a5a06ba30ad2a1c8ebee50efbe5a9267a81270c6f75358d3b4440d2
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