Instructions to use ProbeX/Model-J__SupViT__model_idx_0117 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_0117 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_0117") 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_0117") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0117") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b23c84849a685fd66ad84007ddb77cc8b3d2bcb16701eaa1a7bafdab966933e7
- Size of remote file:
- 5.37 kB
- SHA256:
- 7156d3dceb1f703bb497290756c97d80c586729bf734c8bd1a07134ca7eaf172
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