Instructions to use ProbeX/Model-J__MAE__model_idx_0133 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_0133 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_0133") 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_0133") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0133") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0eea5f500b4390ebefd864778a7484dabceb71ae7297dc51fba84a21f6227a1e
- Size of remote file:
- 5.37 kB
- SHA256:
- 36927ada7d59bff24338ddd1baf5175ba5f25866fa28a195dc9083eb9575e9e5
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