Instructions to use ProbeX/Model-J__DINO__model_idx_0964 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_0964 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_0964") 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_0964") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0964", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68d6ba3e3929e6587b5a9178cae01d28aa4eeb57476c8e144326324b65e6c5b1
- Size of remote file:
- 5.37 kB
- SHA256:
- a832bbef20c3e0c01a652f33726d98e2decd70d8cca6f6981c664d05fba5c2b2
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