Instructions to use ProbeX/Model-J__MAE__model_idx_0641 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_0641 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_0641") 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_0641") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0641", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d85dd069abef64fa0ed5a830260b4accbf65027cecb41bbc7a0218641b798313
- Size of remote file:
- 5.37 kB
- SHA256:
- d86ed527c177c53689e96ed9eac3c52bce289203222cd7c243be2699de9894ec
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