Instructions to use ProbeX/Model-J__DINO__model_idx_0263 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_0263 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_0263") 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_0263") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0263", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91602edbfe8c2c7dbafd7d756c41dd433a5ecee664dc35e84eb70f4df70d291a
- Size of remote file:
- 5.37 kB
- SHA256:
- 818476d233e1cd10bb92720608758f654996e762a9af987d884918d573eced1f
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