Instructions to use ProbeX/Model-J__DINO__model_idx_0548 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_0548 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_0548") 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_0548") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0548") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 852ac6cb412a125a704dcff72c698df8e6f111a65abd7d4a40bad6e417c8f886
- Size of remote file:
- 5.37 kB
- SHA256:
- 388c193d7af7994c66cc5e84503c3b4efeb72a0b0796aa167f17cabd9805c8c8
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