Instructions to use ProbeX/Model-J__MAE__model_idx_0293 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_0293 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_0293") 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_0293") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0293") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a3fcfe9d2f0107a9484bddc2aafcbd69e83327c8f8e99fe2eb4b861537e3edf3
- Size of remote file:
- 5.37 kB
- SHA256:
- 807c89081cc0d32e7c3de40068634adc5fdc5ad20bfc6c54bd9e250d7afd82a5
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