Instructions to use ProbeX/Model-J__SupViT__model_idx_0594 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_0594 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_0594") 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_0594") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0594", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63fc3595e0af00cbfd789f934aab4a9e0086078118daff91c52d3bd34fdfcae9
- Size of remote file:
- 5.37 kB
- SHA256:
- 4936cba98a6639fd0e47946fb4adec951aa79bcdf057b5b4b7d2b5b638db66d7
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