Instructions to use ProbeX/Model-J__ResNet__model_idx_0614 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__ResNet__model_idx_0614 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__ResNet__model_idx_0614") 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__ResNet__model_idx_0614") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0614") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6654c6876f8eccff90de0f6b723d1064a763c7a96963afbebf4a7e2f99be6b8d
- Size of remote file:
- 5.37 kB
- SHA256:
- 6f545d0078ab10a8d570cdffe91346d4caf00a59319c8fdbb6414e4e61a602de
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