Instructions to use ProbeX/Model-J__MAE__model_idx_0844 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_0844 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_0844") 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_0844") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0844") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9022ce18b8637e4d7bcab111d10bbc6d7c4b86bf63e7f505d240defb20fc96e3
- Size of remote file:
- 5.37 kB
- SHA256:
- 3fcbbebdff81312542062dd33d2405b5f965358ce54723885e6a481d4b694dfa
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