Instructions to use ProbeX/Model-J__MAE__model_idx_0636 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_0636 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_0636") 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_0636") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0636", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b4110d0a835694c782d7d71842fdb2247c25c0982606531f915cade944ecf84
- Size of remote file:
- 5.37 kB
- SHA256:
- d4c157e1f6c8cb772c2133451417ad821ab136c2f5242a16aee250c5064a5020
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