Instructions to use ProbeX/Model-J__DINO__model_idx_0963 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_0963 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_0963") 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_0963") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0963", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f238b50b7d20f3145a596e4f23961c50396f319c2d6434c2e4f29f133e451430
- Size of remote file:
- 5.37 kB
- SHA256:
- 1f310e2796761ed27d55508e782fe3e1a19344fe827ef72cdc2aa7662e030876
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