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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bfcd75d50d9e5d0f3a3404a782a436137c07065986dc3dd8ec5008d9484a5d6
- Size of remote file:
- 5.11 kB
- SHA256:
- 961158f45b22f8a49d6265e2cf18cc8e6b490521d318136667e14ab82475b3bd
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