Instructions to use ProbeX/Model-J__DINO__model_idx_0492 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_0492 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_0492") 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_0492") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0492", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14145736deeb911a94c821ec057258891fe998535df1d5f3d4798577323da171
- Size of remote file:
- 5.37 kB
- SHA256:
- 85a7429eacf30d05c7b4a8c2d0572e0e6bc731fe49033fc437d42a132477f534
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