Instructions to use ProbeX/Model-J__DINO__model_idx_0593 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_0593 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_0593") 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_0593") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0593", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a160e3e32c9a71cd417c6f8ab20c97342621b361b861be0bcb4451a75837dfc
- Size of remote file:
- 5.37 kB
- SHA256:
- 601f0516008d7141b569a00d70ade6e771dbae867977541d28c8b2aa3a4acb0a
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