Instructions to use ProbeX/Model-J__DINO__model_idx_0353 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_0353 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_0353") 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_0353") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0353", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4327a269663944f635642884279da1a6bec5c4a8dd3120fb6836a01b1603e4ce
- Size of remote file:
- 5.37 kB
- SHA256:
- 5fe0c8e83579ddbb9f71061f9bb97cc6d14cbdb52c74b660e364283c52624c8d
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