Instructions to use ProbeX/Model-J__MAE__model_idx_0621 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_0621 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_0621") 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_0621") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0621", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4c67401cbd25688edc88d35544b3c8451d7e6de7f6625aa59711d9139163ad7
- Size of remote file:
- 343 MB
- SHA256:
- ec1bffac0d7c767e605611361e76fe1339fb80d9a79414bd3951fb00aa9d6f37
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