Instructions to use ProbeX/Model-J__DINO__model_idx_0968 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_0968 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_0968") 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_0968") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0968") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 589f1be55aa68a89c19231e4a11ab733317210badea1bb77b8effbd8fb2d2b17
- Size of remote file:
- 5.37 kB
- SHA256:
- b0e1870e00aecf86bd9db658d79ec43196394d01123dda4a99ec7add0aa4f2f1
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