Instructions to use PPV/FoodImageClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PPV/FoodImageClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="PPV/FoodImageClassifier") 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("PPV/FoodImageClassifier") model = AutoModelForImageClassification.from_pretrained("PPV/FoodImageClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fedf07602ea5a96a4180bd2560571b8b0638c216f5e28e0a6676b8457bfd37a
- Size of remote file:
- 343 MB
- SHA256:
- bcc578b17bc5e0b15dc8a8af05564ee96da056a3d6734acce5f26b96b5734427
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