Instructions to use ProbeX/Model-J__MAE__model_idx_0934 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_0934 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_0934") 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_0934") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0934", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 165c24314a6e390dde7a3034a824a4f095c5ddb0ba023b7bb041e96384a29b40
- Size of remote file:
- 5.37 kB
- SHA256:
- 34e9ef93dd091f39dd292b4fd0f356ace67bbfd3f895b046a7f0d2535ea5dc86
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