Instructions to use ProbeX/Model-J__MAE__model_idx_0852 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_0852 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_0852") 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_0852") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0852", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a4833da295918ad0909e2d674946a30846793b6f08f02ece4241ed81a302c36e
- Size of remote file:
- 5.37 kB
- SHA256:
- 3ed2f45f855e3a4d4e6304f7bb9e76b3e3680a678f3e6a7dcedabd2c82704d2f
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