Instructions to use ProbeX/Model-J__SupViT__model_idx_0140 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_0140 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_0140", device_map="auto") 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_0140") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0140", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5ce3f6ea6b82fb353647aeed1e9411c772a8db937ad5ed197b84f23016226b8
- Size of remote file:
- 5.37 kB
- SHA256:
- 63df2a6445027edea79b07c442c8e4fd841c73f0e11d76302ceb3b60aca5031c
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