Instructions to use ProbeX/Model-J__MAE__model_idx_0410 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_0410 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_0410") 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_0410") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0410", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a82e1820ce0596e6a889c7fe7a447a8f52fdc8833bd04d8c69d71b1a6e29e36
- Size of remote file:
- 5.37 kB
- SHA256:
- b6c014daf91969e2bf2a92442a4be8d6fb786d0ffac29c6bbad91c13d8967571
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