Instructions to use ProbeX/Model-J__MAE__model_idx_0975 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_0975 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_0975") 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_0975") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0975", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ffcafd7137c095034cba8649a64a53155033869ecf7d675814e2288a826142f8
- Size of remote file:
- 5.37 kB
- SHA256:
- ee9b82508e7853ebce3a4a28f9229d3e43e719a509dd90bb882d0115dc3ce8ce
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