Instructions to use ProbeX/Model-J__SupViT__model_idx_0821 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_0821 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_0821", 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_0821") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0821", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24afd7d0119ff20d4f652c32e233d24094b6919910696d685a48873534373cfd
- Size of remote file:
- 343 MB
- SHA256:
- 92fe6ab79a1331160c5ec0eee13cf801f18c8179a7c275ca975019da58e8805a
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