Instructions to use ProbeX/Model-J__DINO__model_idx_0093 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_0093 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_0093") 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_0093") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0093", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d4fc1ee6d5a3de78586af6091e0eee5da34f33154f8b5cf4c54ff0138c7a8a1
- Size of remote file:
- 5.37 kB
- SHA256:
- 32ee01dec772a671987b233d081492fe03640af8aa3fb7c29062fd49812a518e
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