Instructions to use ProbeX/Model-J__DINO__model_idx_0516 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_0516 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_0516") 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_0516") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0516", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 524175386c05989edada461c1ac4d0dc705a13c0af4d9ddad80ecb9cacde128a
- Size of remote file:
- 5.37 kB
- SHA256:
- 20ac128b90c85945e0ad09dce01967796afe6ca0a455e1f83ae988072c240577
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