Instructions to use ProbeX/Model-J__DINO__model_idx_0433 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_0433 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_0433") 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_0433") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0433") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1caa91790626a07f9e2282e4d2cfeefc801ea54af6464b62ecc95d47ac94957b
- Size of remote file:
- 5.37 kB
- SHA256:
- 6ce4baab7f9c54125c432467e5edf304d49b9cb3be78ddc462a54633cc8f6525
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