Instructions to use ProbeX/Model-J__DINO__model_idx_0582 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_0582 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_0582") 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_0582") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0582", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b48b956b6baeed5af75433af83a755701721700b506c2008ebdfd9859e03a74f
- Size of remote file:
- 5.37 kB
- SHA256:
- 244d27e6c596f238ce6937eb61b38af61fe1fe175e793d79d3dde727bab2f744
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