Instructions to use ProbeX/Model-J__DINO__model_idx_0523 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0523 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0523") 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__DINO__model_idx_0523") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0523") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d85f4d1fa524fb67a91450fe72a3eea7bff11114dff1663db47eb23e2ad46903
- Size of remote file:
- 5.37 kB
- SHA256:
- dd394f3988833b273c63b7a34623e61c3aacfad56ef9b1214e32d18fb3d2b1d6
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