Instructions to use ProbeX/Model-J__SupViT__model_idx_0132 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_0132 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_0132") 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_0132") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0132", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fc82a92f9880df160b0832d6a24299eaa52869f35b623a0e3f39c8f0cf86074
- Size of remote file:
- 5.37 kB
- SHA256:
- e6884bf02acef22ce9a7e7a473f891cb6b29792f2d37dec30d849f7da1569d28
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