Instructions to use ProbeX/Model-J__MAE__model_idx_0505 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_0505 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_0505") 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_0505") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0505") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e385412ed97a9af83498c7e7d1117c96974ea62f1ec8776194af20774e0fc0b1
- Size of remote file:
- 5.37 kB
- SHA256:
- c38870b93ed2e2a1d5530021b73eda7bd0abe915284601b79a08fe16a6b5f37e
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