Instructions to use ProbeX/Model-J__ResNet__model_idx_0107 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_0107 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_0107") 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_0107") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0107") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbce69047d9acdc30ea8711f14cf517f569213768736e2962731d0f56e336699
- Size of remote file:
- 5.37 kB
- SHA256:
- 86ead59e6272bcbb9ab18b2ea9c177e3dbe8c804f9e69a442e61211f5a2d3ece
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