Instructions to use ProbeX/Model-J__DINO__model_idx_0449 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_0449 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_0449") 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_0449") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0449") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd0344ddc8f06dc8025680dc3b6ff9dfff4559cf056e63d0d4db05bbac7364dd
- Size of remote file:
- 5.37 kB
- SHA256:
- 8d7e0cdd754a858ab483e344f76a25690e28f4a66a0c8851f7eee9271cc8f39c
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