Instructions to use ProbeX/Model-J__MAE__model_idx_0469 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_0469 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_0469") 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_0469") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0469", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0d0d52e47bbbd18a424b3d540dc486273f36739c9e7722c5a6c68cf839fdc70
- Size of remote file:
- 5.37 kB
- SHA256:
- c1ed2ac5b24abaa36c53f6d7d6d0f51814778763fd528f4a3e8e5425bb0f0b2a
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