Instructions to use ProbeX/Model-J__SupViT__model_idx_0377 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_0377 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_0377") 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_0377") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0377", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4c2fa24b163a33411552d63d29c407b743d5d7c2416ba1ea77594db83f7b1736
- Size of remote file:
- 5.37 kB
- SHA256:
- d74abea614377145370e00264ffd945c0553bf7d5359f9504a6b3456309082fb
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