Instructions to use ProbeX/Model-J__ResNet__model_idx_0612 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_0612 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_0612") 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_0612") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__ResNet__model_idx_0612") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc145c53b6c2d1bd63373320be6edd843302504163850410b81d16ca015ff807
- Size of remote file:
- 171 MB
- SHA256:
- 4ada2b257e2cf7dee813b9cb590867e128aae64f016f067a466e1b3d39ffad04
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