Instructions to use ProbeX/Model-J__MAE__model_idx_0375 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_0375 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_0375") 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_0375") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0375") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bee0171596a9850438cdbf782a24ebbc632d637f0c8c5a35231a2a3f5014be3b
- Size of remote file:
- 5.37 kB
- SHA256:
- 7da0289131ae4c83ed92c14024a8d7aae47a387a3484bcb0fdbc9bd17ca2eefd
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