Instructions to use ProbeX/Model-J__MAE__model_idx_0513 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_0513 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_0513") 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_0513") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0513") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c68962b89a37fec1d514b513dbee3415906b39603ea16574390b56aa798b4ce
- Size of remote file:
- 5.37 kB
- SHA256:
- 605fc90803aaeef7a96b402f2c09d48d3360d4e7242a21a7ee6f9bf34b41b500
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