Instructions to use ProbeX/Model-J__MAE__model_idx_0719 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_0719 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_0719") 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_0719") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0719") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 153f687b43337601c25b4c6a3f2b1f6c82738ae8bda61e1905de5acc4b88a0c1
- Size of remote file:
- 5.37 kB
- SHA256:
- 763772106221cf195ab6c509f14e95ab7e15632518327cb4c168daa526ee8613
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