Instructions to use ProbeX/Model-J__DINO__model_idx_0252 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_0252 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_0252") 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_0252") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0252", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e35fdfa222492afb6129adb10f8b5a9290843ee1aae8ccb81155005e57c2e1b
- Size of remote file:
- 5.37 kB
- SHA256:
- 3ca3fc9af958b19c68bc26098f0bb0b60089b0fc475036934eada2c5cad24cee
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