Instructions to use ProbeX/Model-J__MAE__model_idx_0921 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_0921 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_0921") 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_0921") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0921") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 573b3b1671850c5cb4e034520ed3e438cdd11a2def96e1a8426ac17e1ebecd1f
- Size of remote file:
- 5.37 kB
- SHA256:
- 0d69ae14e8f1cd8b136794a2f049e6a06ebd80cc536dbf986604f44ca48491c2
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