Instructions to use ProbeX/Model-J__DINO__model_idx_0591 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_0591 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_0591") 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_0591") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0591", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 491c6eca5c6db60dc8d40d219309554dd2363697b08d1d8006766a96c7defaa3
- Size of remote file:
- 5.37 kB
- SHA256:
- 1eb179f2f6ccc4bae44fbf903a9725cb7ab77b57a8dc30c8c533c4fc60da0fa3
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