Instructions to use ProbeX/Model-J__MAE__model_idx_0514 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_0514 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_0514") 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_0514") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0514", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13a5df7275f90466a9100dacb3ff62c1778dad938ec2acf86408696ae037a535
- Size of remote file:
- 5.37 kB
- SHA256:
- e6fd9613b3aacaf1c401270f4d17307d9cbbb5a3a6dff08711d38a672ebd672c
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