Instructions to use ProbeX/Model-J__SupViT__model_idx_0388 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_0388 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_0388") 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_0388") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0388", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d1973d3461eb977ffcd8ddd2bcd7c5b59191268fb86bd7c3e7d8714ae37fb67
- Size of remote file:
- 5.37 kB
- SHA256:
- 216e9a0b42d4b0ec6d5101f4936ce22fe2653e0e1916be8a37088a9458b3c2dc
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