Instructions to use ProbeX/Model-J__SupViT__model_idx_0547 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_0547 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_0547") 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_0547") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0547") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 591adc2fbd80c538ad79fdce1ec0f71a3852819a96c17764c0d59f76e2b51cad
- Size of remote file:
- 5.37 kB
- SHA256:
- 2677985979fa92fe033d09fd39e58400a1f6bca75648e943f85abcdd1417be64
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