Instructions to use ProbeX/Model-J__MAE__model_idx_0708 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_0708 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_0708") 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_0708") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0708") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 566e799ad4eed86871b655f29b4f1d143879fbdc7b9698e1835f3ea415f661a2
- Size of remote file:
- 343 MB
- SHA256:
- eec8281fd96c7bb99694dcd1a4e8804e07771cdc86180a54b7e9680dc80f86fe
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