Instructions to use ProbeX/Model-J__MAE__model_idx_0545 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_0545 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_0545") 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_0545") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0545") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 14953932fd12427e2b3853bdeee6df8ac35f6f256ddde5b777e35ec3b46bb0c9
- Size of remote file:
- 5.37 kB
- SHA256:
- dc562d24c8fbaded2c7904511e7cc9d6f3f46c48c51d59e1c47b145f6fa8cee5
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