Instructions to use ProbeX/Model-J__MAE__model_idx_0116 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_0116 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_0116") 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_0116") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0116", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0986feab48c6a2f96bc4c086365d45dc71b191e46e6e03bec85e566b445098d
- Size of remote file:
- 5.37 kB
- SHA256:
- 6bc781720d812cddfb5b297bb6590085e3b812c04a9a8ca4cf85768e4bfb8a10
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