Instructions to use ProbeX/Model-J__MAE__model_idx_0936 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_0936 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_0936") 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_0936") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0936") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 328b31f1bb5c7901c50006e04793bd861f2e7554c242aa1e26c721bbb72f6f9f
- Size of remote file:
- 5.37 kB
- SHA256:
- 7ef318d38bb7d7063ee3dc74bf9c507416c221969632b6c912b2c7c2c0bb510d
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