Instructions to use ProbeX/Model-J__MAE__model_idx_0880 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_0880 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_0880") 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_0880") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0880", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6392b4dfd712e1f25ac4bd1e0ca73e2970f968c96c95a3ace28a293e1a03c493
- Size of remote file:
- 5.37 kB
- SHA256:
- f2cada3cd2c156e0b8a3c6b376f83ae5a2f6dd6474ba9dd32868573de56e5c88
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