Instructions to use ProbeX/Model-J__MAE__model_idx_0893 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_0893 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_0893") 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_0893") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0893", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da30d00b07255daab7c5d0038fd6bddcd49aa4f96d789ba41d75854451018a8d
- Size of remote file:
- 5.37 kB
- SHA256:
- 28ae369164888830518ad43539cdcb79590d424b06faf2155a7bd55511fa1f0e
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