Instructions to use ProbeX/Model-J__MAE__model_idx_0321 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_0321 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_0321") 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_0321") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0321", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3b67732cc9437ed51fcac3d8f1217df369a2dd1256e6267577a4a16228a8c4f
- Size of remote file:
- 5.37 kB
- SHA256:
- 6899d6304e92e7765cdd11b8d3f8708b63e1c2112e2269feb7469974481aa219
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