Instructions to use ProbeX/Model-J__DINO__model_idx_0852 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_0852 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_0852") 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_0852") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0852") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7a2f221ed48cb1af64ce3752f1185cc553f1c6358dbc009cc3bc3fc5675deac
- Size of remote file:
- 5.37 kB
- SHA256:
- 05620b9726aa4c5234b81dda23db67b6667c151e71ebfa6f86303634be21feca
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