Instructions to use ProbeX/Model-J__MAE__model_idx_0955 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_0955 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_0955") 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_0955") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0955") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 047c5f22d395603e4c78fbbeee4a29fd344d19af0041f01a9112344f3169d7b5
- Size of remote file:
- 5.37 kB
- SHA256:
- 153a25cade7b5b9b4b8e8e9dfd879b714cf2309dbb886d14b22d84656142a30b
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