Instructions to use stchakman/Fridge_Items_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stchakman/Fridge_Items_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="stchakman/Fridge_Items_Model") 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("stchakman/Fridge_Items_Model") model = AutoModelForImageClassification.from_pretrained("stchakman/Fridge_Items_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da76783079ec6a5f2207028f1d755fe9ce3bdeaf31969807d0ea7d036c5993b4
- Size of remote file:
- 344 MB
- SHA256:
- 35acd3d19742f70eaa1500feec73e94a7a87411838093ec696ba81ed3f44d4bc
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