Instructions to use ProbeX/Model-J__MAE__model_idx_0223 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_0223 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_0223") 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_0223") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0223", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c7b9517142cab60a215e6486ff70df2949d6b2b4998e14d9f47f1e81cb715fe
- Size of remote file:
- 5.37 kB
- SHA256:
- 7b995c9ed1ca639de1a7f8dafd8641740771c56c675d532d0be47b4017ea357d
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