Instructions to use ProbeX/Model-J__DINO__model_idx_0850 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_0850 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_0850") 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_0850") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0850") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e087f2be0adfd04dfcae7413113943fcfac8eb325f9b4ecbb04c53ad59dae800
- Size of remote file:
- 5.37 kB
- SHA256:
- 5fb525d954a11dceee9931078da00cdd4386452535cff5918b6e83e4dbbee9bd
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