Instructions to use ProbeX/Model-J__SupViT__model_idx_0782 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_0782 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_0782") 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_0782") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0782", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d74a617bcfdb246ba6ae232cdf82aacfe219e61c30d80a94fb549035f72c5cdf
- Size of remote file:
- 5.37 kB
- SHA256:
- d0125658a1f8e96d68cac0d34555beacaeac212b7c56ea53bb14581be1d67dce
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