Instructions to use ProbeX/Model-J__DINO__model_idx_0489 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_0489 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_0489") 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_0489") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0489", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53eb49073aba21dca36aacc2bc6568fbbf894bacc3dfda478affd68a441fff2e
- Size of remote file:
- 5.37 kB
- SHA256:
- b425869355049aae7c46dcd178913b83e01981ead650fb92b76e1c897c5cc0c7
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