Instructions to use ProbeX/Model-J__DINO__model_idx_0180 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_0180 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_0180") 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_0180") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0180") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 89beaeea8a8a43c9edf13c52e836e34ab4876d8caa3ca184d9bb43123082222f
- Size of remote file:
- 5.37 kB
- SHA256:
- 8b263036b62141429d754cf7badf6b40c9942ace93cb277efbdb78c6f81dec89
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