Instructions to use ProbeX/Model-J__DINO__model_idx_0736 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_0736 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_0736") 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_0736") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0736") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b516fe1125d5bc1bba757c5d24889d6bcef5a1c8e6c494279d07bb4faf05ef9
- Size of remote file:
- 5.37 kB
- SHA256:
- d0edab9dc72130e5076b7862fb90223efb07d705f447e373fd41a11b6ebf1e52
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