Instructions to use ProbeX/Model-J__DINO__model_idx_0485 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_0485 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_0485") 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_0485") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0485", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f42c0be96913aef9732be02981aca9058b75040c2397ff4fc38f7b5ea5c2e7b
- Size of remote file:
- 5.37 kB
- SHA256:
- e45a59e8d8fe850794ea1123f750cd7807c4b48d51e3a95ce48f3def8d4feb5d
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