Instructions to use ProbeX/Model-J__MAE__model_idx_0965 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_0965 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_0965") 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_0965") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0965", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eafa93c46e093bf04fb98d358cb3d8e790cc094ec668b62fa9ff386e7f764a8b
- Size of remote file:
- 5.37 kB
- SHA256:
- f0c08733c963329d436a141937570622d014cc6e9948d74001fa87ced5538e72
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