Instructions to use ProbeX/Model-J__DINO__model_idx_0142 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_0142 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_0142") 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_0142") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0142", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54419c7bc152ee1c6d2c6dbdbe194389e8b5e0fb9122a11edcfab42f58cd8116
- Size of remote file:
- 5.37 kB
- SHA256:
- 3ca5ee903e6deff4a20c1d6fa198199e1d04fa91302019b9c8708cf65237909e
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