Instructions to use ArrayDice/food_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArrayDice/food_image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ArrayDice/food_image_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("ArrayDice/food_image_classification") model = AutoModelForImageClassification.from_pretrained("ArrayDice/food_image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a7aecd0334658b1328f22057b9bca82e79fb5078d00aac8e085b13bcb66e452
- Size of remote file:
- 344 MB
- SHA256:
- 2f724798e852ab5217f23a8751e46597c7b02664762bc3104f791e71ad91b8bc
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