Instructions to use ProbeX/Model-J__DINO__model_idx_0243 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_0243 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_0243") 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_0243") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0243") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85e23fc980031ee315627f2f13255b642337454aeff54fe2294b3871555fe685
- Size of remote file:
- 5.37 kB
- SHA256:
- d6a7210e7ea6e9c42d753891b8c76d53956826e6938b0d3d6f8777c2fc80bb0d
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