Instructions to use ProbeX/Model-J__MAE__model_idx_0826 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_0826 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_0826") 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_0826") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0826", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5abb2e4d0bf146fcc6aa6f8a0fa660c72beb42fb3857779c366d8852d5f5fc7b
- Size of remote file:
- 5.37 kB
- SHA256:
- ea74d9dcc0ac2d4df51ca9d1d190263b6faecd550426acdacb49a60438a68091
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