Instructions to use ProbeX/Model-J__MAE__model_idx_0742 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_0742 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_0742") 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_0742") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0742", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c30147c36619a7c8cd63713c787883160e9aee7a9c11a0eaccdf83f8c6ed810
- Size of remote file:
- 5.37 kB
- SHA256:
- c2d5a6fd29af511c61195185938fee7bd460e4998ef0e61380fa6047f79ceda9
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