Instructions to use ProbeX/Model-J__DINO__model_idx_0791 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_0791 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_0791") 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_0791") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0791") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e8b7f2003452ee040706134ae76669e603d1b76bfab3d9c6cfe14f8e24e73c1
- Size of remote file:
- 5.37 kB
- SHA256:
- 50e83ae4eed7add4b712c102c6ffd22ae6a4ec6b92b949473d3e03a90b8ab6e3
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