Instructions to use ProbeX/Model-J__MAE__model_idx_0861 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_0861 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_0861") 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_0861") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0861", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d18e7075254d66bf843c002cae66f193bd9cbe8667956104e32c9b71bfec0750
- Size of remote file:
- 5.37 kB
- SHA256:
- f6dd266de890ccb2686323f90baa98b6e11681b65f8a063a5f2a35f26bde299f
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