Instructions to use ProbeX/Model-J__ResNet__model_idx_0624 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_0624 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_0624") 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_0624") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0624") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad40c2947b48fcd7c2288e9d299d5684364b95b2ca5c4551fad36f2fd2d7ee2f
- Size of remote file:
- 5.37 kB
- SHA256:
- b45702b6c09a6b8b8d7d4ae0d9ccf17e24ad104ce1e6057d51dd96a001023018
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