Instructions to use ProbeX/Model-J__SupViT__model_idx_0191 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_0191 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_0191") 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_0191") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0191", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5cdcb70c181f76c6f89005db771e20f80f70d8f367f3f1191c86b82caa75e437
- Size of remote file:
- 5.37 kB
- SHA256:
- 330cccd626bb588846f56384e10880121d50e9c86068b27922aad3aede64eb98
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