Instructions to use ProbeX/Model-J__MAE__model_idx_0853 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_0853 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_0853") 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_0853") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0853") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d862177ed595e35a4ed7a09febfabbf119265e14a68bb148d69fe1b014639eb8
- Size of remote file:
- 5.37 kB
- SHA256:
- dfd0787bd2baaec7c694752963d2900d851db9e225ec1891821c1602b17c6205
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