Instructions to use skierdude/pizza_parallel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skierdude/pizza_parallel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="skierdude/pizza_parallel") 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("skierdude/pizza_parallel") model = AutoModelForImageClassification.from_pretrained("skierdude/pizza_parallel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f779bb9f74864acb8f169fe8839672a0e4defa5fac035fce47b8c1d37a9cef0
- Size of remote file:
- 343 MB
- SHA256:
- b68b9f2639b70fcdefaca193951fc66a0aab92f4e5c30233942a06b2a2eaadc7
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