Instructions to use ProbeX/Model-J__MAE__model_idx_0008 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_0008 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_0008") 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_0008") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0008") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e719ddf5c321ab7d12f0095b2575da6497b581149c3502589e5615b5a94d3a6f
- Size of remote file:
- 5.37 kB
- SHA256:
- 2a6466e34fb2319a7bd66aff6bd361ea8eabb6a6a5d7ace827445cac83739fb6
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