Instructions to use ProbeX/Model-J__MAE__model_idx_0253 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_0253 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_0253") 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_0253") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0253", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78304cf9d15918d7cc5e2b736e206615fcc0ca44ea69be77de95cc166300cfc0
- Size of remote file:
- 5.37 kB
- SHA256:
- 7443c486ad8157fa0e00800d690436520ab1b472e201a39102ad146d336ed4b8
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