Instructions to use ProbeX/Model-J__MAE__model_idx_0974 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_0974 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_0974") 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_0974") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0974") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1727e3070ccc8c9d7425a7845a337a7baea342d5d0e3dd148d13f3a2b6590d29
- Size of remote file:
- 5.37 kB
- SHA256:
- b7dada8df68f4c5a73298e8ff87ed186ee96debc0d90b93fdc9a75c9d94c50bc
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