Instructions to use ProbeX/Model-J__ResNet__model_idx_0617 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_0617 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_0617") 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_0617") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0617") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d35ed22adcef8bc4033e5b77f16d7f3d128557d934d86dc6235758d89d99a355
- Size of remote file:
- 5.37 kB
- SHA256:
- ad9ee19dfeb4c9f80c7e01f40a3d998d8f880821828f2b9de7ad785e83b6d582
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