Instructions to use Luke537/image_classification_food_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Luke537/image_classification_food_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Luke537/image_classification_food_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("Luke537/image_classification_food_model") model = AutoModelForImageClassification.from_pretrained("Luke537/image_classification_food_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- edfaec608ef5553c09b86abfc902352fa8c500b7a120e7aa978bd18af5988999
- Size of remote file:
- 344 MB
- SHA256:
- 02b2dc3d33766b9c801ba95f0f48c57735ac53e8dafedb2fb94b6d09c3cc1885
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