Instructions to use ProbeX/Model-J__SupViT__model_idx_0257 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_0257 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_0257") 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_0257") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0257", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 587fbaf7828860adea1c407a3ebdad44229e732b64d190083fa7bb3569b77085
- Size of remote file:
- 5.37 kB
- SHA256:
- c953807ce34d8cb2e34151a1eb66c14e836641be232eb143f1264c19fdef7749
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