Instructions to use ProbeX/Model-J__DINO__model_idx_0704 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_0704 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_0704") 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_0704") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0704") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af6bd670fb3b3dd215db9e6fa6df88292761589944e187e0333e2da42d7c3428
- Size of remote file:
- 5.37 kB
- SHA256:
- da74dc272d80b1aaf22d0b467b12275bb195e12f9aec3836bfb61a8dc5b8d9a5
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