Instructions to use ProbeX/Model-J__ResNet__model_idx_0659 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_0659 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_0659") 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_0659") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0659") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00cfc1a54baef61b9d2d91239bf32ede1e32d1a12ee8dc01488317383582201f
- Size of remote file:
- 5.37 kB
- SHA256:
- f8e5fa8b54d2a442739730a12689cad876e8e7a2cdf4db5097163285b8dd77a5
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