Instructions to use ProbeX/Model-J__MAE__model_idx_0792 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_0792 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_0792") 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_0792") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0792") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- db64011e47c6cf3fda6a7754eb5903be1c0cca2328cce26d2178ddf419b41a87
- Size of remote file:
- 5.37 kB
- SHA256:
- 8c53277852c76eb3761db49b8d4fdd9ab57d23d5a583dc0acca46bb9a1a496e9
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