Instructions to use ProbeX/Model-J__DINO__model_idx_0397 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_0397 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_0397") 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_0397") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0397") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6df4a08237ff70761db19619dfa5388c3b7b412eaf73a1a23c00bf1feccfee92
- Size of remote file:
- 5.37 kB
- SHA256:
- 403b1b50e51820effb20aa99e6f74c256fae4415192bd0d0b0642ce80d0829fd
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