Instructions to use ProbeX/Model-J__MAE__model_idx_0533 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_0533 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_0533") 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_0533") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0533") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d4bf245f2cfdac3c5f69c04b8ecf5937b79c63a12ce942b55251007b763a318
- Size of remote file:
- 5.37 kB
- SHA256:
- 2fd6cb19f86fe1e84d268d8b48798a7eb77172b4659a63d281ec3251ab4ebb35
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