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:
- f5a16c71b1272a56d90179b09698158442ab1ea2a5789d98e7209d373e6cf563
- Size of remote file:
- 343 MB
- SHA256:
- 2d0c18efdd7c7dad64a35700d79e07054828522eeff501bc4b033b1bee1e0364
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