Instructions to use ProbeX/Model-J__DINO__model_idx_0187 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_0187 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_0187") 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_0187") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0187", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bc832ac74a19f5876db5c68ff3f75daa0fe2d579661c8dbbb8ded72e5fe53ab
- Size of remote file:
- 5.37 kB
- SHA256:
- 94dc5f4f83e66e19f05d95ca01fc298632007417f6e04b0568f76dade6e5d2b9
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