Instructions to use ProbeX/Model-J__SupViT__model_idx_0868 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_0868 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_0868") 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_0868") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0868", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d75653c0e6582c5b116c927b873cf6c0a8a5c9f4e7555a019ec4d793606c2bb4
- Size of remote file:
- 343 MB
- SHA256:
- d50354000e05bfa7eaea3196b7f2608a13f2cedf437824ddfdf73dfa4f6b2ee2
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