Instructions to use ProbeX/Model-J__MAE__model_idx_0652 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_0652 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_0652") 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_0652") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0652", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7953e8411b9621e1e033b195b760fe3d8d1ce937d6f970fb68986a50d5c77855
- Size of remote file:
- 5.37 kB
- SHA256:
- bcc56d81d33eceed930ca59ebfa8bbf95fa1a7b0fc8a9faaf3cea17fac0be568
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