Instructions to use ProbeX/Model-J__SupViT__model_idx_0832 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_0832 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_0832") 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_0832") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0832") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50308550a6d5eb66dcb0dc51992d9cee96556beea843a74d54f1715ef49eb55f
- Size of remote file:
- 5.37 kB
- SHA256:
- 4f662b07427ff42f8a647541487ec38bd353dba4419dbcf21251f5a385dc348a
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