Instructions to use ProbeX/Model-J__MAE__model_idx_0144 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_0144 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_0144") 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_0144") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0144") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2741faa7017cebed0d9edc83e4e03fbd58a7ee55731b590d40d97032182e6fbf
- Size of remote file:
- 5.37 kB
- SHA256:
- cb911d47dabc65448f0e72774b87fe429ec82be3d3b532eb0952cfea04c60a7c
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