Instructions to use ProbeX/Model-J__DINO__model_idx_0630 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_0630 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_0630") 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_0630") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0630", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 077b0ac871652e4d57c6bd9c6d1f80f67542f4ec179fe3bec4e1ead82cb2f3af
- Size of remote file:
- 5.37 kB
- SHA256:
- 11a34ac405390ba1fc44aa17ded32bc8292c898c44ef8bfb112c68e2c6e397f9
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