Instructions to use ProbeX/Model-J__MAE__model_idx_0001 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_0001 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_0001") 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_0001") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0001") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7de027beb8e082453fb5d2e9778ef2992e2d7ece698e9dbf040a04aaa1d9bec3
- Size of remote file:
- 5.37 kB
- SHA256:
- 7fc8a0bf8cfef517db5d4a2eb742af2696b9c216515db1ee503a43c11e9bdd1d
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