Instructions to use ProbeX/Model-J__MAE__model_idx_0173 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__MAE__model_idx_0173 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__MAE__model_idx_0173") 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__MAE__model_idx_0173") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0173") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae6bdf3fff0e8b972eac02412b0ba153a1fa71ad0d59d5ca43ff1fb4f38d82fb
- Size of remote file:
- 5.37 kB
- SHA256:
- 95002bd8614b304262731f27b2e114123a2850212bdb4a60ad0fc972030870eb
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