Instructions to use ProbeX/Model-J__ResNet__model_idx_0858 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_0858 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_0858") 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_0858") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0858") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0ba60522b6cbacc6ff4f0e68bd3699c18416c556ae168a6afd4141fe9d9724e
- Size of remote file:
- 5.37 kB
- SHA256:
- 162cb65feb00d05c5291865c2ed9763050038a66d728e1b3e6ba7be41b6b7cd7
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