Instructions to use ProbeX/Model-J__DINO__model_idx_0566 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_0566 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_0566") 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_0566") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0566", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b9cb1b907f6f445931cec4d73faa2f814cc6227024d762f75e002d238304c35
- Size of remote file:
- 5.37 kB
- SHA256:
- bc6bc74e9a73841721199d75a39c27f15b35967fad71118e14ea166e9402432b
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