Instructions to use ProbeX/Model-J__SupViT__model_idx_0059 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_0059 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_0059") 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_0059") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0059") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f2e49771858f1113d41854b6c2ab57969bce1bfb2c6133057e63f2e7121db7a
- Size of remote file:
- 5.37 kB
- SHA256:
- 217f4d6d4d5479f585e2cbf8615d32b7f644b5a00ff2914c2fcddaa110fadfd9
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