Instructions to use ProbeX/Model-J__DINO__model_idx_0929 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_0929 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_0929") 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_0929") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0929") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd3ea405dc745d097cebd1a53ebc26ee53e0c0a2e27651d44b5c737b2b0e09d6
- Size of remote file:
- 5.37 kB
- SHA256:
- e0b443c74de85c1440636e88631e042ae479e0c9a93a615e112dfe00a705070e
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