Instructions to use ProbeX/Model-J__DINO__model_idx_0508 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_0508 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_0508") 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_0508") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0508", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e019e568c01658b4c54a00eec80d194a5bb03c52698fd55ed85e4069f64a69e
- Size of remote file:
- 5.37 kB
- SHA256:
- ca621e0ad284e47a59cb286efa2dcb849758328c8e1eccb8368eaf2643e318f3
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