Instructions to use ProbeX/Model-J__SupViT__model_idx_0338 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_0338 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_0338") 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_0338") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0338") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9eccf1bbc571657e6dece50303e0286ae35311a912c8aa53891e9af360ef581e
- Size of remote file:
- 5.37 kB
- SHA256:
- c632ac7eeb483aabdda7024f1a45e99827fcfc31c263428e6cc73c6899d3e892
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