Instructions to use ProbeX/Model-J__MAE__model_idx_0365 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_0365 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_0365") 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_0365") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0365") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7dd42b63e794848f12b1a4c3da364e873bf86e9888878b6ac07d920e3bd15b3
- Size of remote file:
- 5.37 kB
- SHA256:
- 9f69017cf2f83824302d3df204cbd1360d3987bb919bd8591654a2e46d32d0f5
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