Instructions to use Jacques7103/Food-Recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jacques7103/Food-Recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Jacques7103/Food-Recognition") 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("Jacques7103/Food-Recognition") model = AutoModelForImageClassification.from_pretrained("Jacques7103/Food-Recognition") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01c53e015a9f793de0987ea9fb53670f28f3f1cb67c8241b1a416e3449654b24
- Size of remote file:
- 4.66 kB
- SHA256:
- 890b16bc32dc17c3ec171db6f184d67c2e5fd31aa71375b70b363980e65c3465
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