Instructions to use ProbeX/Model-J__MAE__model_idx_0973 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_0973 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_0973") 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_0973") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0973") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0a167e00d44ab79599459943b2d87e4f285d3d29aa422143d79956e4bc7db5f
- Size of remote file:
- 5.37 kB
- SHA256:
- 2d38faedcb672da2d1863d28ebeca3838c8626761108fc673841f49f7b3602de
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