Instructions to use ProbeX/Model-J__DINO__model_idx_0122 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_0122 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_0122") 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_0122") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0122", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4f9282921528bcc5b74dc3207e796b72bf377efa629baf67e936304afe614d3
- Size of remote file:
- 5.37 kB
- SHA256:
- 674343e3e922179867bad755d812f8476799c7105c1d5dee3c9fac4c01e30c41
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