Instructions to use ProbeX/Model-J__DINO__model_idx_0403 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_0403 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_0403") 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_0403") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0403") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ccc05e573ea87d8c0565ba935d917562326139bad2638fbc53cf2e93bd532ff
- Size of remote file:
- 5.37 kB
- SHA256:
- 55142c61536ea13ec74491d163d11472907cb20f41e79f26b6abe495427dbd7f
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