Instructions to use ProbeX/Model-J__DINO__model_idx_0960 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_0960 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_0960") 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_0960") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0960", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 542671494a8639428822aa5e2b13d664c207a492d1410ced06023fa38ca5db73
- Size of remote file:
- 5.37 kB
- SHA256:
- 8179819df221ef0cda328c1f1f949663b6aa8124086b0c42b316b3fcb846a838
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