Instructions to use ProbeX/Model-J__MAE__model_idx_0772 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_0772 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_0772") 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_0772") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0772") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e825045e1ce71346848b0d4f7154e659fefe0184048513546414f1f1a5bb7831
- Size of remote file:
- 5.37 kB
- SHA256:
- 32afe0be8c098257224ef7bfd5cca1cb53063f0cd8de8e82d23e360402794eb5
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