Instructions to use ProbeX/Model-J__MAE__model_idx_0682 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_0682 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_0682") 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_0682") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0682") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa67d0f805ab8549fe530d6e7101e9ec55b3131a4b3c091ae405d6a617f83cf4
- Size of remote file:
- 5.37 kB
- SHA256:
- bc368ec7cb45f4f5051468de67e61217e82fb9aa3c54b1f6966f80ab7800fed6
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