Instructions to use ProbeX/Model-J__MAE__model_idx_0187 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_0187 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_0187") 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_0187") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0187") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52a0abfcb855c4e498d6a7da8da7ccfc591901a715998815ddb4f2f875ad4c51
- Size of remote file:
- 5.37 kB
- SHA256:
- 217e1083055c678615f29830fa5787553dd5dcbeef907420bfec812ea62b776c
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