Instructions to use ProbeX/Model-J__MAE__model_idx_0882 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_0882 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_0882") 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_0882") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0882") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1249cd49c0dd66f56c82538f029e9f51c7091275f18d6d2cbbcb06075c16d112
- Size of remote file:
- 5.37 kB
- SHA256:
- 3d9fb2f66c4ddf0c4d9e9022d5ef52d852238909a955e6ce7f40a3f998fba830
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