Instructions to use ProbeX/Model-J__DINO__model_idx_0102 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_0102 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_0102") 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_0102") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0102") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3606900bb832a2b489df35656056fd1d9a8d7949afbb4fc3d30119498592d5c
- Size of remote file:
- 5.37 kB
- SHA256:
- e20a7d611f87ff994c36f78931ad689c47ff4c3ae6022988bb34c4fe226a349c
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