Instructions to use ProbeX/Model-J__DINO__model_idx_0946 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_0946 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_0946") 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_0946") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0946") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fcc446f8743e9bc9a45caf9e957f36e69ef02160499e99bfc291ff30883abe28
- Size of remote file:
- 5.37 kB
- SHA256:
- 82edcfa000f096e478075730ced9ce55a031380b17e5222cc64882f177c3a5a0
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