Instructions to use ProbeX/Model-J__MAE__model_idx_0900 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_0900 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_0900") 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_0900") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0900", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb4b13688cf746aa37bd62e54f95339263e3e05d6c0fdf823ba9167c58cd4b4e
- Size of remote file:
- 5.37 kB
- SHA256:
- 8981313e9055ab98d64570480722af3ec7cea2ea7844726c486263744af95037
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