Instructions to use ProbeX/Model-J__MAE__model_idx_0720 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_0720 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_0720") 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_0720") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0720", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd87976e007bbf42894b3e032fa3b0555703f2fc8c83d7dbb46492fae33b85be
- Size of remote file:
- 5.37 kB
- SHA256:
- cc5f48796d13c4c4157e106ba425585fc304e89b27a527f0fd22d606140d0076
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