Instructions to use ProbeX/Model-J__MAE__model_idx_0108 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_0108 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_0108") 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_0108") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0108", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f1183a580e55f1e8345895a4987167acd81deabd683756fe1450129b6dd0291
- Size of remote file:
- 5.37 kB
- SHA256:
- c961a9982c6848267e20c0909d33a54ba8d8d96368ec6a0883070d692a085d36
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