Instructions to use Kaludi/Food-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kaludi/Food-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Kaludi/Food-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("Kaludi/Food-Classification") model = AutoModelForImageClassification.from_pretrained("Kaludi/Food-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9af401d803d30ef70e907b53a8c6665ccbf6d3111a8788dd112bf955fc72a3b7
- Size of remote file:
- 348 MB
- SHA256:
- 8a9e55d0f2fed16dd22f55858e0fc74e5001c032b8a043247742377ac2be868c
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