Instructions to use ProbeX/Model-J__MAE__model_idx_0922 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_0922 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_0922") 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_0922") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0922") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 854a1ed882e129f536d53c07f731b4b67b8ac6d3254efc45bcde8e15ad79cd42
- Size of remote file:
- 5.37 kB
- SHA256:
- 829ebe26621b495c6e5d9bde9303e5d7666b1619d8c5e40648236434eb83850a
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