Instructions to use Kaludi/Food-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kaludi/Food-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Kaludi/Food-Classification") 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("Kaludi/Food-Classification") model = AutoModelForImageClassification.from_pretrained("Kaludi/Food-Classification") - Notebooks
- Google Colab
- Kaggle
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### Gradio
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[](https://huggingface.co/spaces/Kaludi/Food-Classification_App)
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### Gradio
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Tis model supports a [Gradio](https://github.com/gradio-app/gradio) Web UI to run the data-food-classification model:
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[](https://huggingface.co/spaces/Kaludi/Food-Classification_App)
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